Abstract

This tutorial offers an introduction to terrestrial and close-range hyperspectral imaging and some of its uses in human color vision research. The main types of hyperspectral cameras are described together with procedures for image acquisition, postprocessing, and calibration for either radiance or reflectance data. Image transformations are defined for colorimetric representations, color rendering, and cone receptor and postreceptor coding. Several example applications are also presented. These include calculating the color properties of scenes, such as gamut volume and metamerism, and analyzing the utility of color in observer tasks, such as identifying surfaces under illuminant changes. The effects of noise and uncertainty are considered in both image acquisition and color vision applications.

Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Full Article  |  PDF Article
OSA Recommended Articles
The Verriest Lecture: Color vision in an uncertain world

David H. Foster
J. Opt. Soc. Am. A 35(4) B192-B201 (2018)

The number of discernible colors in natural scenes

João Manuel Maciel Linhares, Paulo Daniel Pinto, and Sérgio Miguel Cardoso Nascimento
J. Opt. Soc. Am. A 25(12) 2918-2924 (2008)

Use of commercial off-the-shelf digital cameras for scientific data acquisition and scene-specific color calibration

Derya Akkaynak, Tali Treibitz, Bei Xiao, Umut A. Gürkan, Justine J. Allen, Utkan Demirci, and Roger T. Hanlon
J. Opt. Soc. Am. A 31(2) 312-321 (2014)

References

  • View by:
  • |
  • |
  • |

  1. H. F. Grahn and P. Geladi, eds., Techniques and Applications of Hyperspectral Image Analysis (Wiley, 2007).
  2. N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013).
    [Crossref]
  3. L. Arend, “Environmental challenges to color constancy,” in Human Vision and Electronic Imaging VI, B. E. Rogowitz and T. N. Pappas, eds. (SPIE, 2001), pp. 392–399.
  4. Munsell Color Company, Munsell Book of Color–Matte Finish Collection (Munsell Color Corporation, 1976).
  5. J. Hernández-Andrés, J. Romero, and J. L. Nieves, “Color and spectral analysis of daylight in southern Europe,” J. Opt. Soc. Am. A 18, 1325–1335 (2001).
    [Crossref]
  6. UNESCO, International Classification and Mapping of Vegetation (UNESCO, 1973).
  7. Federal Geographic Data Committee, “Vegetation classification standard,” U.S. Geological Survey, , 1997.
  8. D. H. Foster, K. Amano, S. M. C. Nascimento, and M. J. Foster, “Frequency of metamerism in natural scenes,” J. Opt. Soc. Am. A 23, 2359–2372 (2006).
    [Crossref]
  9. F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, Geometrical considerations and nomenclature for reflectance (Institute for Basic Standards/National Bureau of Standards, 1997).
  10. C. L. Wyatt, V. Privalsky, and R. Datla, Recommended practice: symbols, terms, units and uncertainty analysis for radiometric sensor calibration (National Institute of Standards and Technology, U.S. Department of Commerce Technology Administration, 1998).
  11. W. L. Wolfe, “Glossary and fundamental constants,” in Handbook of Optics, Volume 1, Geometrical and Physical Optics, Polarized Light, Components and Instruments, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. xxix–xxxiv.
  12. CIE, “A colour appearance model for colour management systems: CIECAM02,” CIE Central Bureau, , 2004.
  13. CIE, “Colorimetry, 4th Edition,” CIE Central Bureau, , 2018.
  14. F. Gori and P. S. Carney, “Introducing JOSA A tutorials: editorial,” J. Opt. Soc. Am. A 32, ED3 (2015).
    [Crossref]
  15. V. C. Coffey, “Hyperspectral imaging for safety and security,” Opt. Photon. News 26, 28–33 (2015).
  16. T. H. Kurz and S. J. Buckley, “A review of hyperspectral imaging in close range applications,” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XLI-B5, 865–870 (2016).
    [Crossref]
  17. Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
    [Crossref]
  18. S. K. Shevell, ed., The Science of Color, 2nd ed. (Elsevier, 2003).
  19. D. H. Brainard and A. Stockman, “Colorimetry,” in Handbook of Optics. Volume III. Vision and Vision Optics, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 10.1–10.56.
  20. D. H. Foster, “Chromatic function of the cones,” in Encyclopedia of the Eye, D. A. Dartt, ed. (Academic, 2010), pp. 266–274.
  21. S. Westland, C. Ripamonti, and V. Cheung, Computational Colour Science Using Matlab, 2nd ed. (Wiley, 2012).
  22. M. D. Fairchild, Color Appearance Models, 2nd ed. (Wiley, 2013).
  23. K. Barnard and B. Funt, “Camera characterization for color research,” Color Res. Appl. 27, 152–163 (2002).
    [Crossref]
  24. V. C. Cardei and B. Funt, “Color correcting uncalibrated digital images,” J. Imaging Sci. Technol. 44, 288–378 (2000).
  25. J. Y. Hardeberg, F. Schmitt, and H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41, 2532–2548 (2002).
    [Crossref]
  26. P. Geladi, J. Burger, and T. Lestlander, “Hyperspectral imaging: calibration problems and solutions,” Chemom. Intell. Lab. Syst. 72, 209–217 (2004).
    [Crossref]
  27. M. Brady and G. E. Legge, “Camera calibration for natural image studies and vision research,” J. Opt. Soc. Am. A 26, 30–42 (2009).
    [Crossref]
  28. M. A. López-Álvarez, J. Hernández-Andrés, J. Romero, J. Campos, and A. Pons, “Calibrating the elements of a multispectral imaging system,” J. Imaging Sci. Technol. 53, 031102 (2009).
    [Crossref]
  29. N. Ekpenyong, Hyperspectral Imaging: Calibration and Applications with Natural Scenes (School of Electrical and Electronic Engineering University of Manchester, 2013).
  30. P. Ziemer, “Design and implementation of a multispectral imaging system,” M.Sc. thesis (Department of Computer Science and Information Science, Universität Konstanz, 2013).
  31. J. R. Janesick, Photon Transfer DN → λ (SPIE, 2007).
  32. S. B. Howell, Handbook of CCD Astronomy, 2nd ed., Cambridge Observing Handbooks for Research Astronomers (Cambridge University, 2006).
  33. S. Le Moan and P. Urban, “Image-difference prediction: from color to spectral,” IEEE Trans. Image Process. 23, 2058–2068 (2014).
    [Crossref]
  34. J. M. M. Linhares, P. D. A. Pinto, and S. M. C. Nascimento, “Color rendering of art paintings under CIE illuminants for normal and color deficient observers,” J. Opt. Soc. Am. A 26, 1668–1677 (2009).
    [Crossref]
  35. C. Montagner, J. M. M. Linhares, M. Vilarigues, and S. M. C. Nascimento, “Statistics of colors in paintings and natural scenes,” J. Opt. Soc. Am. A 33, A170–A177 (2016).
    [Crossref]
  36. S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
    [Crossref]
  37. H. A. Khan, S. Mihoubi, B. Mathon, J.-B. Thomas, and J. Y. Hardeberg, “HyTexiLa: high resolution visible and near infrared hyperspectral texture images,” Sensors 18, 2045 (2018).
    [Crossref]
  38. R. Ennis, F. Schiller, M. Toscani, and K. R. Gegenfurtner, “Hyperspectral database of fruits and vegetables,” J. Opt. Soc. Am. A 35, B256–B266 (2018).
    [Crossref]
  39. K. S. Babu, V. Ramachandran, K. K. Thyagharajan, and G. Santhosh, “Hyperspectral image compression algorithms—a review,” in International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES), L. P. Suresh, S. S. Dash, and B. K. Panigrahi, eds. (Springer, 2015), Vol. 2, pp. 127–138.
  40. M. Paul, R. Xiao, J. B. Gao, and T. Bossomaier, “Reflectance prediction modelling for residual-based hyperspectral image coding,” PLoS ONE 11, e0161212 (2016).
    [Crossref]
  41. R. Dusselaar and M. Paul, “Hyperspectral image compression approaches: opportunities, challenges, and future directions: discussion,” J. Opt. Soc. Am. A 34, 2170–2180 (2017).
    [Crossref]
  42. M. Zucco, M. Pisani, V. Caricato, and A. Egidi, “A hyperspectral imager based on a Fabry–Perot interferometer with dielectric mirrors,” Opt. Express 22, 1824–1834 (2014).
    [Crossref]
  43. L. Gao and L. V. Wang, “A review of snapshot multidimensional optical imaging: measuring photon tags in parallel,” Phys. Rep. 616, 1–37 (2016).
    [Crossref]
  44. T. Hakala, J. Suomalainen, S. Kaasalainen, and Y.-W. Chen, “Full waveform hyperspectral LiDAR for terrestrial laser scanning,” Opt. Express 20, 7119–7127 (2012).
    [Crossref]
  45. F. H. Imai and R. S. Berns, “Spectral estimation using trichromatic digital cameras,” in International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42–49.
  46. E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera and colored filters,” Color Res. Appl. 32, 352–360 (2007).
    [Crossref]
  47. J. L. Nieves, E. M. Valero, J. Hernández-Andrés, and J. Romero, “Recovering fluorescent spectra with an RGB digital camera and color filters using different matrix factorizations,” Appl. Opt. 46, 4144–4154 (2007).
    [Crossref]
  48. F. H. Imai, M. R. Rosen, and R. S. Berns, “Comparison of spectrally narrow-band capture versus wide-band with a priori sample analysis for spectral reflectance estimation,” in Eighth Color Imaging Conference: Color Science and Engineering: Systems, Technologies and Applications (Society for Imaging Science and Technology, 2000), pp. 234–241.
  49. J. M. Lerner, N. Gat, and E. Wachman, “Approaches to spectral imaging hardware,” Curr. Protoc. Cytom. 53, 12–20 (2010).
    [Crossref]
  50. J. Eckhard, T. Eckhard, E. M. Valero, J. L. Nieves, and E. G. Contreras, “Outdoor scene reflectance measurements using a Bragg-grating-based hyperspectral imager,” Appl. Opt. 54, D15–D24 (2015).
    [Crossref]
  51. D. Bannon, “Hyperspectral imaging: cubes and slices,” Nat. Photonics 3, 627–629 (2009).
    [Crossref]
  52. M. Vakalopoulou and K. Karantzalos, “Automatic descriptor-based co-registration of frame hyperspectral data,” Remote Sens. 6, 3409–3426 (2014).
    [Crossref]
  53. P. Jerram, D. Burt, D. Morris, T. Eaton, and M. Fryer, “Design of image sensors for hyperspectral applications,” in Sensors, Systems, and Next-Generation Satellites XIII, R. Meynart, S. P. Neeck, and H. Shimoda, eds. (SPIE, 2009), pp. 74741E1.
  54. L. Galvis, H. Arguello, and G. R. Arce, “Coded aperture design in mismatched compressive spectral imaging,” Appl. Opt. 54, 9875–9882 (2015).
    [Crossref]
  55. X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
    [Crossref]
  56. X.-B. Wang, P. J. Green, J.-B. Thomas, J. Y. Hardeberg, and P. Gouton, “Evaluation of the colorimetric performance of single-sensor image acquisition systems employing colour and multispectral filter array,” in Computational Color Imaging, CCIW, A. Trémeau, R. Schettini, and S. Tominaga, eds. (Springer, 2015), pp. 181–191.
  57. C. V. Correa, C. A. Hinojosa, G. R. Arce, and H. Arguello, “Multiple snapshot colored compressive spectral imager,” Opt. Eng. 56, 041309 (2016).
    [Crossref]
  58. L.-L. Qian, Q.-B. Lü, M. Huang, Q.-S. Cai, and B. Xiang-li, “Effect of keystone on coded aperture spectral imaging,” Optik 127, 686–689 (2016).
    [Crossref]
  59. R. Zhen and R. L. Stevenson, “Image demosaicing,” in Color Image and Video Enhancement, M. E. Celebi, M. Lecca, and B. Smolka, eds. (Springer, 2015), pp. 13–22.
  60. A. Mansouri, F. S. Marzani, and P. Gouton, “Development of a protocol for CCD calibration: application to a multispectral imaging system,” Int. J. Robot. Autom. 20, 94–100 (2005).
  61. H. Liang, “Advances in multispectral and hyperspectral imaging for archaeology and art conservation,” Appl. Phys. A 106, 309–323 (2012).
    [Crossref]
  62. M. R. Pointer, G. G. Attridge, and R. E. Jacobson, “Practical camera characterization for colour measurement,” Imaging Sci. J. 49, 63–80 (2001).
    [Crossref]
  63. V. Cheung and S. Westland, “Methods for optimal color selection,” J. Imaging Sci. Technol. 50, 481–488 (2006).
    [Crossref]
  64. J. M. Palmer, “Radiometry and photometry: units and conversions,” in Handbook of Optics, Volume II, Design, Fabrication, and Testing; Sources and Detectors; Radiometry and Photometry, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 36.1–36.19.
  65. T. Luhmann, C. Fraser, and H.-G. Maas, “Sensor modelling and camera calibration for close-range photogrammetry,” ISPRS J. Photogramm. Remote Sens. 115, 37–46 (2016).
    [Crossref]
  66. J. Salvi, X. Armangué, and J. Batlle, “A comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recogn. 35, 1617–1635 (2002).
    [Crossref]
  67. T. F. Blake, S. C. Cain, and M. E. Goda, “Enhancing the resolution of spectral images from the advanced electro-optical system spectral imaging sensor,” Opt. Eng. 46, 057001 (2007).
    [Crossref]
  68. F. Toadere, “Simulating the functionality of a digital camera pipeline,” Opt. Eng. 52, 102005 (2013).
    [Crossref]
  69. S. Watanabe, T. Takahashi, and K. Bennett, “Quantitative evaluation of the accuracy and variance of individual pixels in a scientific CMOS (sCMOS) camera for computational imaging,” Proc. SPIE 10071, 100710Z (2017).
    [Crossref]
  70. J. Burger and P. Geladi, “Hyperspectral NIR image regression, part I: calibration and correction,” J. Chemom. 19, 355–363 (2005).
    [Crossref]
  71. P. A. Jansson and R. P. Breault, “Correcting color-measurement error caused by stray light in image scanners,” in Sixth Color and Imaging Conference: Color Science, Systems, and Applications (Society for Imaging Science and Technology, 1998), pp. 69–73.
  72. S. Helling, “Improvement of multispectral image capture by compensating for stray light,” in CGIV 2006, 3rd European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2006), pp. 458–462.
  73. H. S. Fairman, “An improved method for correcting radiance data for bandpass error,” Color Res. Appl. 35, 328–333 (2010).
    [Crossref]
  74. N. Gat, “Imaging spectroscopy using tunable filters: a review,” Proc. SPIE 4056, 50–64 (2000).
    [Crossref]
  75. R. Kingslake and R. B. Johnson, Lens Design Fundamentals, 2nd ed. (Academic/SPIE, 2010).
  76. B. Zitová and J. Flusser, “Image registration methods: a survey,” Image Vis. Comput. 21, 977–1000 (2003).
    [Crossref]
  77. T. Eckhard, J. Eckhard, E. M. Valero, and J. L. Nieves, “Nonrigid registration with free-form deformation model of multilevel uniform cubic B-splines: application to image registration and distortion correction of spectral image cubes,” Appl. Opt. 53, 3764–3772 (2014).
    [Crossref]
  78. L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
    [Crossref]
  79. D. G. Abdelsalam, M. Stanislas, and S. Coudert, “CCD or CMOS camera calibration using point spread function,” Proc. SPIE 9234, 92340Z (2014).
    [Crossref]
  80. E. Buhr, S. Günther-Kohfahl, and U. Neitzel, “Simple method for modulation transfer function determination of digital imaging detectors from edge images,” Proc. SPIE 5030, 877–884 (2003).
    [Crossref]
  81. J. Brauers, C. Seiler, and T. Aach, “Direct PSF estimation using a random noise target,” Proc. SPIE 7537, 75370B (2010).
    [Crossref]
  82. J. R. Miller, S. C. Jain, N. T. O’Neill, W. R. McNeil, and K. P. B. Thomson, “Interpretation of airborne spectral reflectance measurements over Georgian Bay,” Remote Sens. Environ. 6, 183–200 (1977).
    [Crossref]
  83. D. H. Brainard and L. T. Maloney, “Surface color perception and equivalent illumination models,” J. Vis. 11(5), 1 (2011).
    [Crossref]
  84. H. A. Khan, J.-B. Thomas, J. Y. Hardeberg, and O. Laligant, “Illuminant estimation in multispectral imaging,” J. Opt. Soc. Am. A 34, 1085–1098 (2017).
    [Crossref]
  85. B. V. Funt, M. S. Drew, and J. Ho, “Color constancy from mutual reflection,” Int. J. Comput. Vis. 6, 5–24 (1991).
    [Crossref]
  86. S. Tominaga, K. Kato, K. Hirai, and T. Horiuchi, “Spectral image analysis of mutual illumination between florescent objects,” J. Opt. Soc. Am. A 33, 1476–1487 (2016).
    [Crossref]
  87. B. V. Funt and M. S. Drew, “Color space analysis of mutual illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1319–1326 (1993).
    [Crossref]
  88. R. Deeb, D. Muselet, M. Hebert, and A. Tremeau, “Interreflections in computer vision: a survey and an introduction to spectral infinite-bounce model,” J. Math. Imaging Vis. 60, 661–680 (2018).
    [Crossref]
  89. H. K. Lichtenthaler and U. Rinderle, “The role of chlorophyll fluorescence in the detection of stress conditions in plants,” CRC Crit. Rev. Anal. Chem. 19, S29–S85 (1988).
    [Crossref]
  90. P. K. E. Campbell, E. M. Middleton, L. A. Corp, and M. S. Kim, “Contribution of chlorophyll fluorescence to the apparent vegetation reflectance,” Sci. Total Environ. 404, 433–439 (2008).
    [Crossref]
  91. G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing—definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006).
    [Crossref]
  92. G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).
  93. D. H. Foster, K. Amano, and S. M. C. Nascimento, “Time-lapse ratios of cone excitations in natural scenes,” Vis. Res. 120, 45–60(2016).
    [Crossref]
  94. A. Gijsenij, R. Lu, and T. Gevers, “Color constancy for multiple light sources,” IEEE Trans. Image Process. 21, 697–707 (2012).
    [Crossref]
  95. L. Gu, C. P. Huynh, and A. Robles-Kelly, “Segmentation and estimation of spatially varying illumination,” IEEE Trans. Image Process. 23, 3478–3489 (2014).
    [Crossref]
  96. R. C. Love, Surface Reflection Model Estimation from Naturally Illuminated Image Sequences (School of Computer Studies, University of Leeds, 1997).
  97. J. H. McClendon, “The micro-optics of leaves. I. Patterns of reflection from the epidermis,” Am. J. Bot. 71, 1391–1397 (1984).
    [Crossref]
  98. D. A. Sims and J. A. Gamon, “Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages,” Remote Sens. Environ. 81, 337–354 (2002).
    [Crossref]
  99. D. Lee, Nature’s Palette: The Science of Plant Color (University of Chicago, 2007).
  100. J. B. Clark and G. R. Lister, “Photosynthetic action spectra of trees. II. The relationship of cuticle structure to the visible and ultraviolet spectral properties of needles from four coniferous species,” Plant Physiol. 55, 407–413 (1975).
    [Crossref]
  101. J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. I. Introduction and the correction of leaf spectra for surface reflection,” Photochem. Photobiol. 51, 203–210 (1990).
    [Crossref]
  102. J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. II. The non-absorbed ray of the sieve effect and the mean optical pathlength in the remainder of the leaf,” Photochem. Photobiol. 51, 211–216 (1990).
    [Crossref]
  103. S. M. C. Nascimento, K. Amano, and D. H. Foster, “Spatial distributions of local illumination color in natural scenes,” Vis. Res. 120, 39–44 (2016).
    [Crossref]
  104. R. Heylen, M. Parente, and P. Gader, “A review of nonlinear hyperspectral unmixing methods,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 7, 1844–1868 (2014).
    [Crossref]
  105. J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
    [Crossref]
  106. D. K. Prasad and L. Wenhe, “Metrics and statistics of frequency of occurrence of metamerism in consumer cameras for natural scenes,” J. Opt. Soc. Am. A 32, 1390–1402 (2015).
    [Crossref]
  107. R. Bala, G. Finlayson, and C. Lee, “Computational color imaging,” in Handbook of Convex Optimization Methods in Imaging Science, V. Monga, ed. (Springer, 2017), pp. 43–70.
  108. H. Terstiege, “Chromatic adaptation: a state-of-the-art report,” J. Color Appearance 1, 19–23, 40 (1972).
  109. G. D. Finlayson, M. S. Drew, and B. V. Funt, “Spectral sharpening: sensor transformations for improved color constancy,” J. Opt. Soc. Am. A 11, 1553–1563 (1994).
    [Crossref]
  110. C. Li, M. R. Luo, B. Rigg, and R. W. G. Hunt, “CMC 2000 chromatic adaptation transform: CMCCAT2000,” Color Res. Appl. 27, 49–58 (2002).
    [Crossref]
  111. K. A. G. Smet, M. A. Webster, and L. A. Whitehead, “A simple principled approach for modeling and understanding uniform color metrics,” J. Opt. Soc. Am. A 33, A319–A331 (2016).
    [Crossref]
  112. M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
    [Crossref]
  113. M. Melgosa, R. Huertas, and R. S. Berns, “Performance of recent advanced color-difference formulas using the standardized residual sum of squares index,” J. Opt. Soc. Am. A 25, 1828–1834 (2008).
    [Crossref]
  114. M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31, 320–330 (2006).
    [Crossref]
  115. C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
    [Crossref]
  116. E. Reinhard, E. A. Khan, A. O. Akyüz, and G. M. Johnson, Color Imaging: Fundamentals and Applications (A. K. Peters, 2008).
  117. S. Le Moan, A. Mansouri, Y. Voisin, and J. Y. Hardeberg, “A constrained band selection method based on information measures for spectral image color visualization,” IEEE Trans. Geosci. Remote Sens. 49, 5104–5115 (2011).
    [Crossref]
  118. IEC, “Colour management in multimedia systems–Part 2: colour management, Part 2.1: default RGB colour space–sRGB,” International Electrotechnical Commission, , 1998.
  119. W. Cowan, “Displays for vision research,” in Handbook of Optics. Volume III. Vision and Vision Optics, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 22.1–22.41.
  120. D. H. Foster, “Color constancy,” Vis. Res. 51, 674–700 (2011).
    [Crossref]
  121. W. K. Pratt, Digital Image Processing, 4th ed. (Wiley, 2007).
  122. J. Morovič, Color Gamut Mapping (Wiley, 2008).
  123. A. Stockman and L. T. Sharpe, “Cone spectral sensitivities and color matching,” in Color Vision: From Genes To Perception, K. R. Gegenfurtner and L. T. Sharpe, eds. (Cambridge University, 1999), pp. 53–87.
  124. A. Stockman, L. T. Sharpe, and C. Fach, “The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches,” Vis. Res. 39, 2901–2927 (1999).
    [Crossref]
  125. A. Stockman and L. T. Sharpe, “The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype,” Vision Res. 40, 1711–1737 (2000).
    [Crossref]
  126. T. D. Lamb, “Why rods and cones?” Eye 30, 179–185 (2016).
    [Crossref]
  127. A. J. Zele and D. Cao, “Vision under mesopic and scotopic illumination,” Front. Psychol. 5, 1594, 1–15 (2015).
    [Crossref]
  128. D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
    [Crossref]
  129. P. A. Barrionuevo and D. C. Cao, “Contributions of rhodopsin, cone opsins, and melanopsin to postreceptoral pathways inferred from natural image statistics,” J. Opt. Soc. Am. A 31, A131–A139(2014).
    [Crossref]
  130. B. R. Conway, R. T. Eskew, P. R. Martin, and A. Stockman, “A tour of contemporary color vision research,” Vis. Res. 151, 2–6 (2018).
    [Crossref]
  131. D. L. Ruderman, T. W. Cronin, and C.-C. Chiao, “Statistics of cone responses to natural images: implications for visual coding,” J. Opt. Soc. Am. A 15, 2036–2045 (1998).
    [Crossref]
  132. G. Buchsbaum and A. Gottschalk, “Trichromacy, opponent colours coding and optimum colour information transmission in the retina,” Proc. R. Soc. London B 220, 89–113 (1983).
    [Crossref]
  133. T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Color opponency is an efficient representation of spectral properties in natural scenes,” Vis. Res. 42, 2095–2103 (2002).
    [Crossref]
  134. J. J. Vos and P. L. Walraven, “On the derivation of the foveal receptor primaries,” Vis. Res. 11, 799–818 (1970).
    [Crossref]
  135. D. M. Mount and S. Arya, “ANN: a library for approximate nearest neighbor searching, version 1.1.2,” (University of Maryland, 2010).
  136. S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, “An optimal algorithm for approximate nearest neighbor searching in fixed dimensions,” J. ACM 45, 891–923 (1998).
    [Crossref]
  137. D. H. Foster, I. Marín-Franch, K. Amano, and S. M. C. Nascimento, “Approaching ideal observer efficiency in using color to retrieve information from natural scenes,” J. Opt. Soc. Am. A 26, B14–B24 (2009).
    [Crossref]
  138. S. K. Shevell and P. R. Martin, “Color opponency: tutorial,” J. Opt. Soc. Am. A 34, 1099–1108 (2017).
    [Crossref]
  139. R. Shapley and M. J. Hawken, “Color in the cortex: single- and double-opponent cells,” Vision Res. 51, 701–717 (2011).
    [Crossref]
  140. D. I. A. MacLeod and R. M. Boynton, “Chromaticity diagram showing cone excitation by stimuli of equal luminance,” J. Opt. Soc. Am. 69, 1183–1186 (1979).
    [Crossref]
  141. A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. 357, 241–265 (1984).
    [Crossref]
  142. X. Zhang, D. A. Silverstein, J. E. Farrell, and B. A. Wandell, “Color image quality metric S-CIELAB and its application on halftone texture visibility,” in IEEE COMPCON 97 (IEEE, 1997), pp. 44–48.
  143. G. M. Johnson and M. D. Fairchild, “A top down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
    [Crossref]
  144. C. A. Párraga, G. Brelstaff, T. Troscianko, and I. R. Moorehead, “Color and luminance information in natural scenes,” J. Opt. Soc. Am. A 15, 563–569 (1998).
    [Crossref]
  145. I. Fine, D. I. A. MacLeod, and G. M. Boynton, “Surface segmentation based on the luminance and color statistics of natural scenes,” J. Opt. Soc. Am. A 20, 1283–1291 (2003).
    [Crossref]
  146. E. Doi, T. Inue, T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Spatiochromatic receptive field properties derived from information-theoretic analyses of cone mosaic responses to natural scenes,” Neural Comput. 15, 397–417 (2003).
    [Crossref]
  147. E. Provenzi, J. Delon, Y. Gousseau, and B. Mazin, “On the second order spatiochromatic structure of natural images,” Vis. Res. 120, 22–38 (2016).
    [Crossref]
  148. D. H. Foster, “The Verriest lecture: color vision in an uncertain world,” J. Opt. Soc. Am. A 35, B192–B201 (2018).
    [Crossref]
  149. M. R. Pointer and G. G. Attridge, “The number of discernible colours,” Color Res. Appl. 23, 52–54 (1998).
    [Crossref]
  150. F. Martínez-Verdú, E. Perales, E. Chorro, D. de Fez, V. Viqueira, and E. Gilabert, “Computation and visualization of the MacAdam limits for any lightness, hue angle, and light source,” J. Opt. Soc. Am. A 24, 1501–1515 (2007).
    [Crossref]
  151. M. Flinkman, H. Laamanen, P. Vahimaa, and M. Hauta-Kasari, “Number of colors generated by smooth nonfluorescent reflectance spectra,” J. Opt. Soc. Am. A 29, 2566–2575 (2012).
    [Crossref]
  152. J. Morovic, V. Cheung, and P. Morovic, “Why we don’t know how many colors there are,” in CGIV 2012, 6th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2012), pp. 49–53.
  153. I. Marín-Franch and D. H. Foster, “Number of perceptually distinct surface colors in natural scenes,” J. Vis. 10(9), 9 (2010).
    [Crossref]
  154. B. Hill, T. Roger, and F. W. Vorhagen, “Comparative analysis of the quantization of color spaces on the basis of the CIELAB color-difference formula,” ACM Trans. Graph. 16, 109–154 (1997).
    [Crossref]
  155. W. S. Mokrzycki and M. Tatol, “Colour difference ΔE–a survey,” Mach. Graph. Vis. 20, 383–411 (2011).
  156. P.-L. Sun and J. Morovic, “Inter-relating colour difference metrics,” in Tenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications (Society for Imaging Science and Technology, 2002), pp. 55–60.
  157. S. Westland, University of Leeds (personal communication, 2018).
  158. Y. Li, S. Westland, Q. Pan, and V. Cheung, “Methods to assess the relative number of discernible colors for displays,” in 22nd Color and Imaging Conference (Society for Imaging Science and Technology, 2014), pp. 151–154.
  159. J. M. M. Linhares, P. D. Pinto, and S. M. C. Nascimento, “The number of discernible colors in natural scenes,” J. Opt. Soc. Am. A 25, 2918–2924 (2008).
    [Crossref]
  160. D. L. MacAdam, “Note on the number of distinct chromaticities,” J. Opt. Soc. Am. 37, 308–309 (1947).
    [Crossref]
  161. A. Akbarinia and K. R. Gegenfurtner, “Color metamerism and the structure of illuminant space,” J. Opt. Soc. Am. A 35, B231–B238 (2018).
    [Crossref]
  162. T. M. Cover and J. A. Thomas, Elements of Information Theory, 2nd ed. (Wiley, 2006).
  163. J. M. M. Linhares, P. E. R. Felgueiras, P. D. Pinto, and S. M. C. Nascimento, “Colour rendering of indoor lighting with CIE illuminants and white LEDs for normal and colour deficient observers,” Ophthalmic Physiolog. Opt. 30, 618–625 (2010).
    [Crossref]
  164. A. M. Bakke, I. Farup, and J. Y. Hardeberg, “Evaluation of algorithms for the determination of color gamut boundaries,” J. Imaging Sci. Technol. 54, 050502 (2010).
    [Crossref]
  165. P. Urban, “Gamut volume,” in Encyclopedia of Color Science and Technology, M. R. Luo, ed. (Springer, 2016), pp. 676–678.
  166. H. E. Smithson, “Sensory, computational and cognitive components of human colour constancy,” Philos. Trans. R. Soc. B. 360, 1329–1346 (2005).
    [Crossref]
  167. C. Witzel and K. R. Gegenfurtner, “Color perception: objects, constancy, and categories,” Annu. Rev. Vis. Sci. 4, 475–499 (2018).
    [Crossref]
  168. A. Gijsenij, T. Gevers, and J. van de Weijer, “Computational color constancy: survey and experiments,” IEEE Trans. Image Process. 20, 2475–2489 (2011).
    [Crossref]
  169. M. R. Luo and R. W. G. Hunt, “A chromatic adaptation transform and a colour inconstancy index,” Color Res. Appl. 23, 154–158 (1998).
    [Crossref]
  170. L. E. Arend, A. Reeves, J. Schirillo, and R. Goldstein, “Simultaneous color constancy: papers with diverse Munsell values,” J. Opt. Soc. Am. A 8, 661–672 (1991).
    [Crossref]
  171. D. H. Brainard, “Color constancy in the nearly natural image. 2. Achromatic loci,” J. Opt. Soc. Am. A 15, 307–325 (1998).
    [Crossref]
  172. Y. Ling and A. Hurlbert, “Role of color memory in successive color constancy,” J. Opt. Soc. Am. A 25, 1215–1226 (2008).
    [Crossref]
  173. J. Roca-Vila, C. A. Parraga, and M. Vanrell, “Chromatic settings and the structural color constancy index,” J. Vis. 13 (4), 3 (2013).
    [Crossref]
  174. J. L. Nieves and J. Romero, “Heuristic analysis influence of saliency in the color diversity of natural images,” Color Res. Appl. 43, 713–725 (2018).
    [Crossref]
  175. I. Marín-Franch and D. H. Foster, “Estimating Information from image colors: an application to digital cameras and natural scenes,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 78–91 (2013).
    [Crossref]
  176. G. J. Klir, Uncertainty and Information: Foundations of Generalized Information Theory (Wiley, 2006).
  177. C. Arndt, Information Measures: Information and its Description in Science and Engineering (Springer, 2001).
  178. D. J. C. MacKay, Information Theory, Inference, and Learning Algorithms (Cambridge University, 2003).
  179. M. Grendar, “Entropy and effective support size,” Entropy 8, 169–174 (2006).
    [Crossref]
  180. G. Feng and D. H. Foster, “Predicting frequency of metamerism in natural scenes by entropy of colors,” J. Opt. Soc. Am. A 29, A200–A208 (2012).
    [Crossref]
  181. N. Fider and N. L. Komarova, “Quantitative study of color category boundaries,” J. Opt. Soc. Am. A 35, B165–B183 (2018).
    [Crossref]
  182. A. Lewis and L. Zhaoping, “Are cone sensitivities determined by natural color statistics?” J. Vis. 6 (3), 285–302 (2006).
    [Crossref]
  183. A. Lapidoth, “Nearest neighbor decoding for additive non-Gaussian noise channels,” IEEE Trans. Inf. Theory 42, 1520–1529 (1996).
    [Crossref]
  184. T. Morimoto and H. E. Smithson, “Discrimination of spectral reflectance under environmental illumination,” J. Opt. Soc. Am. A 35, B244–B255 (2018).
    [Crossref]
  185. D. H. Foster and K. Żychaluk, “Is there a better non-parametric alternative to von Kries scaling?” in CGIV 2008, 4th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2008), pp. 41–44.
  186. R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, “The mutual information: detecting and evaluating dependencies between variables,” Bioinformatics 18, S231–S240 (2002).
    [Crossref]
  187. L. F. Kozachenko and N. N. Leonenko, “Sample estimate of the entropy of a random vector,” Probl. Inf. Transm. 23, 95–101(1987).
  188. M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. Novi Inverardi, “A new class of random vector entropy estimators and its applications in testing statistical hypotheses,” J. Nonparametr. Stat. 17, 277–297 (2005).
    [Crossref]

2018 (10)

H. A. Khan, S. Mihoubi, B. Mathon, J.-B. Thomas, and J. Y. Hardeberg, “HyTexiLa: high resolution visible and near infrared hyperspectral texture images,” Sensors 18, 2045 (2018).
[Crossref]

R. Ennis, F. Schiller, M. Toscani, and K. R. Gegenfurtner, “Hyperspectral database of fruits and vegetables,” J. Opt. Soc. Am. A 35, B256–B266 (2018).
[Crossref]

R. Deeb, D. Muselet, M. Hebert, and A. Tremeau, “Interreflections in computer vision: a survey and an introduction to spectral infinite-bounce model,” J. Math. Imaging Vis. 60, 661–680 (2018).
[Crossref]

B. R. Conway, R. T. Eskew, P. R. Martin, and A. Stockman, “A tour of contemporary color vision research,” Vis. Res. 151, 2–6 (2018).
[Crossref]

D. H. Foster, “The Verriest lecture: color vision in an uncertain world,” J. Opt. Soc. Am. A 35, B192–B201 (2018).
[Crossref]

A. Akbarinia and K. R. Gegenfurtner, “Color metamerism and the structure of illuminant space,” J. Opt. Soc. Am. A 35, B231–B238 (2018).
[Crossref]

C. Witzel and K. R. Gegenfurtner, “Color perception: objects, constancy, and categories,” Annu. Rev. Vis. Sci. 4, 475–499 (2018).
[Crossref]

J. L. Nieves and J. Romero, “Heuristic analysis influence of saliency in the color diversity of natural images,” Color Res. Appl. 43, 713–725 (2018).
[Crossref]

N. Fider and N. L. Komarova, “Quantitative study of color category boundaries,” J. Opt. Soc. Am. A 35, B165–B183 (2018).
[Crossref]

T. Morimoto and H. E. Smithson, “Discrimination of spectral reflectance under environmental illumination,” J. Opt. Soc. Am. A 35, B244–B255 (2018).
[Crossref]

2017 (7)

S. K. Shevell and P. R. Martin, “Color opponency: tutorial,” J. Opt. Soc. Am. A 34, 1099–1108 (2017).
[Crossref]

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

H. A. Khan, J.-B. Thomas, J. Y. Hardeberg, and O. Laligant, “Illuminant estimation in multispectral imaging,” J. Opt. Soc. Am. A 34, 1085–1098 (2017).
[Crossref]

S. Watanabe, T. Takahashi, and K. Bennett, “Quantitative evaluation of the accuracy and variance of individual pixels in a scientific CMOS (sCMOS) camera for computational imaging,” Proc. SPIE 10071, 100710Z (2017).
[Crossref]

L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
[Crossref]

R. Dusselaar and M. Paul, “Hyperspectral image compression approaches: opportunities, challenges, and future directions: discussion,” J. Opt. Soc. Am. A 34, 2170–2180 (2017).
[Crossref]

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

2016 (14)

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

C. V. Correa, C. A. Hinojosa, G. R. Arce, and H. Arguello, “Multiple snapshot colored compressive spectral imager,” Opt. Eng. 56, 041309 (2016).
[Crossref]

L.-L. Qian, Q.-B. Lü, M. Huang, Q.-S. Cai, and B. Xiang-li, “Effect of keystone on coded aperture spectral imaging,” Optik 127, 686–689 (2016).
[Crossref]

M. Paul, R. Xiao, J. B. Gao, and T. Bossomaier, “Reflectance prediction modelling for residual-based hyperspectral image coding,” PLoS ONE 11, e0161212 (2016).
[Crossref]

L. Gao and L. V. Wang, “A review of snapshot multidimensional optical imaging: measuring photon tags in parallel,” Phys. Rep. 616, 1–37 (2016).
[Crossref]

T. H. Kurz and S. J. Buckley, “A review of hyperspectral imaging in close range applications,” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XLI-B5, 865–870 (2016).
[Crossref]

C. Montagner, J. M. M. Linhares, M. Vilarigues, and S. M. C. Nascimento, “Statistics of colors in paintings and natural scenes,” J. Opt. Soc. Am. A 33, A170–A177 (2016).
[Crossref]

T. Luhmann, C. Fraser, and H.-G. Maas, “Sensor modelling and camera calibration for close-range photogrammetry,” ISPRS J. Photogramm. Remote Sens. 115, 37–46 (2016).
[Crossref]

S. Tominaga, K. Kato, K. Hirai, and T. Horiuchi, “Spectral image analysis of mutual illumination between florescent objects,” J. Opt. Soc. Am. A 33, 1476–1487 (2016).
[Crossref]

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Time-lapse ratios of cone excitations in natural scenes,” Vis. Res. 120, 45–60(2016).
[Crossref]

K. A. G. Smet, M. A. Webster, and L. A. Whitehead, “A simple principled approach for modeling and understanding uniform color metrics,” J. Opt. Soc. Am. A 33, A319–A331 (2016).
[Crossref]

S. M. C. Nascimento, K. Amano, and D. H. Foster, “Spatial distributions of local illumination color in natural scenes,” Vis. Res. 120, 39–44 (2016).
[Crossref]

T. D. Lamb, “Why rods and cones?” Eye 30, 179–185 (2016).
[Crossref]

E. Provenzi, J. Delon, Y. Gousseau, and B. Mazin, “On the second order spatiochromatic structure of natural images,” Vis. Res. 120, 22–38 (2016).
[Crossref]

2015 (6)

2014 (8)

M. Zucco, M. Pisani, V. Caricato, and A. Egidi, “A hyperspectral imager based on a Fabry–Perot interferometer with dielectric mirrors,” Opt. Express 22, 1824–1834 (2014).
[Crossref]

S. Le Moan and P. Urban, “Image-difference prediction: from color to spectral,” IEEE Trans. Image Process. 23, 2058–2068 (2014).
[Crossref]

M. Vakalopoulou and K. Karantzalos, “Automatic descriptor-based co-registration of frame hyperspectral data,” Remote Sens. 6, 3409–3426 (2014).
[Crossref]

D. G. Abdelsalam, M. Stanislas, and S. Coudert, “CCD or CMOS camera calibration using point spread function,” Proc. SPIE 9234, 92340Z (2014).
[Crossref]

L. Gu, C. P. Huynh, and A. Robles-Kelly, “Segmentation and estimation of spatially varying illumination,” IEEE Trans. Image Process. 23, 3478–3489 (2014).
[Crossref]

T. Eckhard, J. Eckhard, E. M. Valero, and J. L. Nieves, “Nonrigid registration with free-form deformation model of multilevel uniform cubic B-splines: application to image registration and distortion correction of spectral image cubes,” Appl. Opt. 53, 3764–3772 (2014).
[Crossref]

R. Heylen, M. Parente, and P. Gader, “A review of nonlinear hyperspectral unmixing methods,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 7, 1844–1868 (2014).
[Crossref]

P. A. Barrionuevo and D. C. Cao, “Contributions of rhodopsin, cone opsins, and melanopsin to postreceptoral pathways inferred from natural image statistics,” J. Opt. Soc. Am. A 31, A131–A139(2014).
[Crossref]

2013 (5)

I. Marín-Franch and D. H. Foster, “Estimating Information from image colors: an application to digital cameras and natural scenes,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 78–91 (2013).
[Crossref]

J. Roca-Vila, C. A. Parraga, and M. Vanrell, “Chromatic settings and the structural color constancy index,” J. Vis. 13 (4), 3 (2013).
[Crossref]

F. Toadere, “Simulating the functionality of a digital camera pipeline,” Opt. Eng. 52, 102005 (2013).
[Crossref]

N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013).
[Crossref]

Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
[Crossref]

2012 (6)

T. Hakala, J. Suomalainen, S. Kaasalainen, and Y.-W. Chen, “Full waveform hyperspectral LiDAR for terrestrial laser scanning,” Opt. Express 20, 7119–7127 (2012).
[Crossref]

H. Liang, “Advances in multispectral and hyperspectral imaging for archaeology and art conservation,” Appl. Phys. A 106, 309–323 (2012).
[Crossref]

A. Gijsenij, R. Lu, and T. Gevers, “Color constancy for multiple light sources,” IEEE Trans. Image Process. 21, 697–707 (2012).
[Crossref]

G. Feng and D. H. Foster, “Predicting frequency of metamerism in natural scenes by entropy of colors,” J. Opt. Soc. Am. A 29, A200–A208 (2012).
[Crossref]

M. Flinkman, H. Laamanen, P. Vahimaa, and M. Hauta-Kasari, “Number of colors generated by smooth nonfluorescent reflectance spectra,” J. Opt. Soc. Am. A 29, 2566–2575 (2012).
[Crossref]

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

2011 (6)

S. Le Moan, A. Mansouri, Y. Voisin, and J. Y. Hardeberg, “A constrained band selection method based on information measures for spectral image color visualization,” IEEE Trans. Geosci. Remote Sens. 49, 5104–5115 (2011).
[Crossref]

D. H. Foster, “Color constancy,” Vis. Res. 51, 674–700 (2011).
[Crossref]

R. Shapley and M. J. Hawken, “Color in the cortex: single- and double-opponent cells,” Vision Res. 51, 701–717 (2011).
[Crossref]

A. Gijsenij, T. Gevers, and J. van de Weijer, “Computational color constancy: survey and experiments,” IEEE Trans. Image Process. 20, 2475–2489 (2011).
[Crossref]

W. S. Mokrzycki and M. Tatol, “Colour difference ΔE–a survey,” Mach. Graph. Vis. 20, 383–411 (2011).

D. H. Brainard and L. T. Maloney, “Surface color perception and equivalent illumination models,” J. Vis. 11(5), 1 (2011).
[Crossref]

2010 (6)

J. Brauers, C. Seiler, and T. Aach, “Direct PSF estimation using a random noise target,” Proc. SPIE 7537, 75370B (2010).
[Crossref]

H. S. Fairman, “An improved method for correcting radiance data for bandpass error,” Color Res. Appl. 35, 328–333 (2010).
[Crossref]

J. M. Lerner, N. Gat, and E. Wachman, “Approaches to spectral imaging hardware,” Curr. Protoc. Cytom. 53, 12–20 (2010).
[Crossref]

J. M. M. Linhares, P. E. R. Felgueiras, P. D. Pinto, and S. M. C. Nascimento, “Colour rendering of indoor lighting with CIE illuminants and white LEDs for normal and colour deficient observers,” Ophthalmic Physiolog. Opt. 30, 618–625 (2010).
[Crossref]

A. M. Bakke, I. Farup, and J. Y. Hardeberg, “Evaluation of algorithms for the determination of color gamut boundaries,” J. Imaging Sci. Technol. 54, 050502 (2010).
[Crossref]

I. Marín-Franch and D. H. Foster, “Number of perceptually distinct surface colors in natural scenes,” J. Vis. 10(9), 9 (2010).
[Crossref]

2009 (5)

2008 (4)

2007 (4)

F. Martínez-Verdú, E. Perales, E. Chorro, D. de Fez, V. Viqueira, and E. Gilabert, “Computation and visualization of the MacAdam limits for any lightness, hue angle, and light source,” J. Opt. Soc. Am. A 24, 1501–1515 (2007).
[Crossref]

T. F. Blake, S. C. Cain, and M. E. Goda, “Enhancing the resolution of spectral images from the advanced electro-optical system spectral imaging sensor,” Opt. Eng. 46, 057001 (2007).
[Crossref]

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera and colored filters,” Color Res. Appl. 32, 352–360 (2007).
[Crossref]

J. L. Nieves, E. M. Valero, J. Hernández-Andrés, and J. Romero, “Recovering fluorescent spectra with an RGB digital camera and color filters using different matrix factorizations,” Appl. Opt. 46, 4144–4154 (2007).
[Crossref]

2006 (6)

D. H. Foster, K. Amano, S. M. C. Nascimento, and M. J. Foster, “Frequency of metamerism in natural scenes,” J. Opt. Soc. Am. A 23, 2359–2372 (2006).
[Crossref]

V. Cheung and S. Westland, “Methods for optimal color selection,” J. Imaging Sci. Technol. 50, 481–488 (2006).
[Crossref]

G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing—definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006).
[Crossref]

M. Grendar, “Entropy and effective support size,” Entropy 8, 169–174 (2006).
[Crossref]

A. Lewis and L. Zhaoping, “Are cone sensitivities determined by natural color statistics?” J. Vis. 6 (3), 285–302 (2006).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31, 320–330 (2006).
[Crossref]

2005 (5)

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. Novi Inverardi, “A new class of random vector entropy estimators and its applications in testing statistical hypotheses,” J. Nonparametr. Stat. 17, 277–297 (2005).
[Crossref]

H. E. Smithson, “Sensory, computational and cognitive components of human colour constancy,” Philos. Trans. R. Soc. B. 360, 1329–1346 (2005).
[Crossref]

J. Burger and P. Geladi, “Hyperspectral NIR image regression, part I: calibration and correction,” J. Chemom. 19, 355–363 (2005).
[Crossref]

A. Mansouri, F. S. Marzani, and P. Gouton, “Development of a protocol for CCD calibration: application to a multispectral imaging system,” Int. J. Robot. Autom. 20, 94–100 (2005).

2004 (1)

P. Geladi, J. Burger, and T. Lestlander, “Hyperspectral imaging: calibration problems and solutions,” Chemom. Intell. Lab. Syst. 72, 209–217 (2004).
[Crossref]

2003 (5)

B. Zitová and J. Flusser, “Image registration methods: a survey,” Image Vis. Comput. 21, 977–1000 (2003).
[Crossref]

E. Buhr, S. Günther-Kohfahl, and U. Neitzel, “Simple method for modulation transfer function determination of digital imaging detectors from edge images,” Proc. SPIE 5030, 877–884 (2003).
[Crossref]

I. Fine, D. I. A. MacLeod, and G. M. Boynton, “Surface segmentation based on the luminance and color statistics of natural scenes,” J. Opt. Soc. Am. A 20, 1283–1291 (2003).
[Crossref]

E. Doi, T. Inue, T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Spatiochromatic receptive field properties derived from information-theoretic analyses of cone mosaic responses to natural scenes,” Neural Comput. 15, 397–417 (2003).
[Crossref]

G. M. Johnson and M. D. Fairchild, “A top down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
[Crossref]

2002 (7)

T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Color opponency is an efficient representation of spectral properties in natural scenes,” Vis. Res. 42, 2095–2103 (2002).
[Crossref]

C. Li, M. R. Luo, B. Rigg, and R. W. G. Hunt, “CMC 2000 chromatic adaptation transform: CMCCAT2000,” Color Res. Appl. 27, 49–58 (2002).
[Crossref]

D. A. Sims and J. A. Gamon, “Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages,” Remote Sens. Environ. 81, 337–354 (2002).
[Crossref]

R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, “The mutual information: detecting and evaluating dependencies between variables,” Bioinformatics 18, S231–S240 (2002).
[Crossref]

J. Salvi, X. Armangué, and J. Batlle, “A comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recogn. 35, 1617–1635 (2002).
[Crossref]

J. Y. Hardeberg, F. Schmitt, and H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41, 2532–2548 (2002).
[Crossref]

K. Barnard and B. Funt, “Camera characterization for color research,” Color Res. Appl. 27, 152–163 (2002).
[Crossref]

2001 (3)

J. Hernández-Andrés, J. Romero, and J. L. Nieves, “Color and spectral analysis of daylight in southern Europe,” J. Opt. Soc. Am. A 18, 1325–1335 (2001).
[Crossref]

M. R. Pointer, G. G. Attridge, and R. E. Jacobson, “Practical camera characterization for colour measurement,” Imaging Sci. J. 49, 63–80 (2001).
[Crossref]

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[Crossref]

2000 (3)

A. Stockman and L. T. Sharpe, “The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype,” Vision Res. 40, 1711–1737 (2000).
[Crossref]

N. Gat, “Imaging spectroscopy using tunable filters: a review,” Proc. SPIE 4056, 50–64 (2000).
[Crossref]

V. C. Cardei and B. Funt, “Color correcting uncalibrated digital images,” J. Imaging Sci. Technol. 44, 288–378 (2000).

1999 (1)

A. Stockman, L. T. Sharpe, and C. Fach, “The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches,” Vis. Res. 39, 2901–2927 (1999).
[Crossref]

1998 (6)

D. L. Ruderman, T. W. Cronin, and C.-C. Chiao, “Statistics of cone responses to natural images: implications for visual coding,” J. Opt. Soc. Am. A 15, 2036–2045 (1998).
[Crossref]

S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, “An optimal algorithm for approximate nearest neighbor searching in fixed dimensions,” J. ACM 45, 891–923 (1998).
[Crossref]

C. A. Párraga, G. Brelstaff, T. Troscianko, and I. R. Moorehead, “Color and luminance information in natural scenes,” J. Opt. Soc. Am. A 15, 563–569 (1998).
[Crossref]

D. H. Brainard, “Color constancy in the nearly natural image. 2. Achromatic loci,” J. Opt. Soc. Am. A 15, 307–325 (1998).
[Crossref]

M. R. Pointer and G. G. Attridge, “The number of discernible colours,” Color Res. Appl. 23, 52–54 (1998).
[Crossref]

M. R. Luo and R. W. G. Hunt, “A chromatic adaptation transform and a colour inconstancy index,” Color Res. Appl. 23, 154–158 (1998).
[Crossref]

1997 (1)

B. Hill, T. Roger, and F. W. Vorhagen, “Comparative analysis of the quantization of color spaces on the basis of the CIELAB color-difference formula,” ACM Trans. Graph. 16, 109–154 (1997).
[Crossref]

1996 (1)

A. Lapidoth, “Nearest neighbor decoding for additive non-Gaussian noise channels,” IEEE Trans. Inf. Theory 42, 1520–1529 (1996).
[Crossref]

1994 (1)

1993 (1)

B. V. Funt and M. S. Drew, “Color space analysis of mutual illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1319–1326 (1993).
[Crossref]

1991 (2)

1990 (2)

J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. I. Introduction and the correction of leaf spectra for surface reflection,” Photochem. Photobiol. 51, 203–210 (1990).
[Crossref]

J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. II. The non-absorbed ray of the sieve effect and the mean optical pathlength in the remainder of the leaf,” Photochem. Photobiol. 51, 211–216 (1990).
[Crossref]

1988 (1)

H. K. Lichtenthaler and U. Rinderle, “The role of chlorophyll fluorescence in the detection of stress conditions in plants,” CRC Crit. Rev. Anal. Chem. 19, S29–S85 (1988).
[Crossref]

1987 (1)

L. F. Kozachenko and N. N. Leonenko, “Sample estimate of the entropy of a random vector,” Probl. Inf. Transm. 23, 95–101(1987).

1984 (2)

A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. 357, 241–265 (1984).
[Crossref]

J. H. McClendon, “The micro-optics of leaves. I. Patterns of reflection from the epidermis,” Am. J. Bot. 71, 1391–1397 (1984).
[Crossref]

1983 (1)

G. Buchsbaum and A. Gottschalk, “Trichromacy, opponent colours coding and optimum colour information transmission in the retina,” Proc. R. Soc. London B 220, 89–113 (1983).
[Crossref]

1979 (1)

1977 (1)

J. R. Miller, S. C. Jain, N. T. O’Neill, W. R. McNeil, and K. P. B. Thomson, “Interpretation of airborne spectral reflectance measurements over Georgian Bay,” Remote Sens. Environ. 6, 183–200 (1977).
[Crossref]

1975 (1)

J. B. Clark and G. R. Lister, “Photosynthetic action spectra of trees. II. The relationship of cuticle structure to the visible and ultraviolet spectral properties of needles from four coniferous species,” Plant Physiol. 55, 407–413 (1975).
[Crossref]

1972 (1)

H. Terstiege, “Chromatic adaptation: a state-of-the-art report,” J. Color Appearance 1, 19–23, 40 (1972).

1970 (1)

J. J. Vos and P. L. Walraven, “On the derivation of the foveal receptor primaries,” Vis. Res. 11, 799–818 (1970).
[Crossref]

1947 (1)

Aach, T.

J. Brauers, C. Seiler, and T. Aach, “Direct PSF estimation using a random noise target,” Proc. SPIE 7537, 75370B (2010).
[Crossref]

Abdelsalam, D. G.

D. G. Abdelsalam, M. Stanislas, and S. Coudert, “CCD or CMOS camera calibration using point spread function,” Proc. SPIE 9234, 92340Z (2014).
[Crossref]

Akbarinia, A.

Akyüz, A. O.

E. Reinhard, E. A. Khan, A. O. Akyüz, and G. M. Johnson, Color Imaging: Fundamentals and Applications (A. K. Peters, 2008).

Alfaro, C.

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

Amano, K.

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

S. M. C. Nascimento, K. Amano, and D. H. Foster, “Spatial distributions of local illumination color in natural scenes,” Vis. Res. 120, 39–44 (2016).
[Crossref]

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Time-lapse ratios of cone excitations in natural scenes,” Vis. Res. 120, 45–60(2016).
[Crossref]

D. H. Foster, I. Marín-Franch, K. Amano, and S. M. C. Nascimento, “Approaching ideal observer efficiency in using color to retrieve information from natural scenes,” J. Opt. Soc. Am. A 26, B14–B24 (2009).
[Crossref]

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera and colored filters,” Color Res. Appl. 32, 352–360 (2007).
[Crossref]

D. H. Foster, K. Amano, S. M. C. Nascimento, and M. J. Foster, “Frequency of metamerism in natural scenes,” J. Opt. Soc. Am. A 23, 2359–2372 (2006).
[Crossref]

Arce, G. R.

C. V. Correa, C. A. Hinojosa, G. R. Arce, and H. Arguello, “Multiple snapshot colored compressive spectral imager,” Opt. Eng. 56, 041309 (2016).
[Crossref]

L. Galvis, H. Arguello, and G. R. Arce, “Coded aperture design in mismatched compressive spectral imaging,” Appl. Opt. 54, 9875–9882 (2015).
[Crossref]

Arend, L.

L. Arend, “Environmental challenges to color constancy,” in Human Vision and Electronic Imaging VI, B. E. Rogowitz and T. N. Pappas, eds. (SPIE, 2001), pp. 392–399.

Arend, L. E.

Arguello, H.

C. V. Correa, C. A. Hinojosa, G. R. Arce, and H. Arguello, “Multiple snapshot colored compressive spectral imager,” Opt. Eng. 56, 041309 (2016).
[Crossref]

L. Galvis, H. Arguello, and G. R. Arce, “Coded aperture design in mismatched compressive spectral imaging,” Appl. Opt. 54, 9875–9882 (2015).
[Crossref]

Armangué, X.

J. Salvi, X. Armangué, and J. Batlle, “A comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recogn. 35, 1617–1635 (2002).
[Crossref]

Arndt, C.

C. Arndt, Information Measures: Information and its Description in Science and Engineering (Springer, 2001).

Arya, S.

S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, “An optimal algorithm for approximate nearest neighbor searching in fixed dimensions,” J. ACM 45, 891–923 (1998).
[Crossref]

D. M. Mount and S. Arya, “ANN: a library for approximate nearest neighbor searching, version 1.1.2,” (University of Maryland, 2010).

Attridge, G. G.

M. R. Pointer, G. G. Attridge, and R. E. Jacobson, “Practical camera characterization for colour measurement,” Imaging Sci. J. 49, 63–80 (2001).
[Crossref]

M. R. Pointer and G. G. Attridge, “The number of discernible colours,” Color Res. Appl. 23, 52–54 (1998).
[Crossref]

Babu, K. S.

K. S. Babu, V. Ramachandran, K. K. Thyagharajan, and G. Santhosh, “Hyperspectral image compression algorithms—a review,” in International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES), L. P. Suresh, S. S. Dash, and B. K. Panigrahi, eds. (Springer, 2015), Vol. 2, pp. 127–138.

Bailão, A.

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

Bakke, A. M.

A. M. Bakke, I. Farup, and J. Y. Hardeberg, “Evaluation of algorithms for the determination of color gamut boundaries,” J. Imaging Sci. Technol. 54, 050502 (2010).
[Crossref]

Bala, R.

R. Bala, G. Finlayson, and C. Lee, “Computational color imaging,” in Handbook of Convex Optimization Methods in Imaging Science, V. Monga, ed. (Springer, 2017), pp. 43–70.

Bannon, D.

D. Bannon, “Hyperspectral imaging: cubes and slices,” Nat. Photonics 3, 627–629 (2009).
[Crossref]

Barnard, K.

K. Barnard and B. Funt, “Camera characterization for color research,” Color Res. Appl. 27, 152–163 (2002).
[Crossref]

Barrionuevo, P. A.

Batlle, J.

J. Salvi, X. Armangué, and J. Batlle, “A comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recogn. 35, 1617–1635 (2002).
[Crossref]

Bennett, K.

S. Watanabe, T. Takahashi, and K. Bennett, “Quantitative evaluation of the accuracy and variance of individual pixels in a scientific CMOS (sCMOS) camera for computational imaging,” Proc. SPIE 10071, 100710Z (2017).
[Crossref]

Berns, R. S.

M. Melgosa, R. Huertas, and R. S. Berns, “Performance of recent advanced color-difference formulas using the standardized residual sum of squares index,” J. Opt. Soc. Am. A 25, 1828–1834 (2008).
[Crossref]

F. H. Imai and R. S. Berns, “Spectral estimation using trichromatic digital cameras,” in International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42–49.

F. H. Imai, M. R. Rosen, and R. S. Berns, “Comparison of spectrally narrow-band capture versus wide-band with a priori sample analysis for spectral reflectance estimation,” in Eighth Color Imaging Conference: Color Science and Engineering: Systems, Technologies and Applications (Society for Imaging Science and Technology, 2000), pp. 234–241.

Bioucas-Dias, J. M.

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

Blake, T. F.

T. F. Blake, S. C. Cain, and M. E. Goda, “Enhancing the resolution of spectral images from the advanced electro-optical system spectral imaging sensor,” Opt. Eng. 46, 057001 (2007).
[Crossref]

Bossomaier, T.

M. Paul, R. Xiao, J. B. Gao, and T. Bossomaier, “Reflectance prediction modelling for residual-based hyperspectral image coding,” PLoS ONE 11, e0161212 (2016).
[Crossref]

Boynton, G. M.

Boynton, R. M.

Brady, D. J.

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

Brady, M.

Brainard, D. H.

D. H. Brainard and L. T. Maloney, “Surface color perception and equivalent illumination models,” J. Vis. 11(5), 1 (2011).
[Crossref]

D. H. Brainard, “Color constancy in the nearly natural image. 2. Achromatic loci,” J. Opt. Soc. Am. A 15, 307–325 (1998).
[Crossref]

D. H. Brainard and A. Stockman, “Colorimetry,” in Handbook of Optics. Volume III. Vision and Vision Optics, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 10.1–10.56.

Brauers, J.

J. Brauers, C. Seiler, and T. Aach, “Direct PSF estimation using a random noise target,” Proc. SPIE 7537, 75370B (2010).
[Crossref]

Breault, R. P.

P. A. Jansson and R. P. Breault, “Correcting color-measurement error caused by stray light in image scanners,” in Sixth Color and Imaging Conference: Color Science, Systems, and Applications (Society for Imaging Science and Technology, 1998), pp. 69–73.

Brelstaff, G.

Brettel, H.

J. Y. Hardeberg, F. Schmitt, and H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41, 2532–2548 (2002).
[Crossref]

Brill, M. H.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

Buchsbaum, G.

G. Buchsbaum and A. Gottschalk, “Trichromacy, opponent colours coding and optimum colour information transmission in the retina,” Proc. R. Soc. London B 220, 89–113 (1983).
[Crossref]

Buckley, S. J.

T. H. Kurz and S. J. Buckley, “A review of hyperspectral imaging in close range applications,” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XLI-B5, 865–870 (2016).
[Crossref]

Buhr, E.

E. Buhr, S. Günther-Kohfahl, and U. Neitzel, “Simple method for modulation transfer function determination of digital imaging detectors from edge images,” Proc. SPIE 5030, 877–884 (2003).
[Crossref]

Burger, J.

J. Burger and P. Geladi, “Hyperspectral NIR image regression, part I: calibration and correction,” J. Chemom. 19, 355–363 (2005).
[Crossref]

P. Geladi, J. Burger, and T. Lestlander, “Hyperspectral imaging: calibration problems and solutions,” Chemom. Intell. Lab. Syst. 72, 209–217 (2004).
[Crossref]

Burt, D.

P. Jerram, D. Burt, D. Morris, T. Eaton, and M. Fryer, “Design of image sensors for hyperspectral applications,” in Sensors, Systems, and Next-Generation Satellites XIII, R. Meynart, S. P. Neeck, and H. Shimoda, eds. (SPIE, 2009), pp. 74741E1.

Cai, Q.-S.

L.-L. Qian, Q.-B. Lü, M. Huang, Q.-S. Cai, and B. Xiang-li, “Effect of keystone on coded aperture spectral imaging,” Optik 127, 686–689 (2016).
[Crossref]

Cain, S. C.

T. F. Blake, S. C. Cain, and M. E. Goda, “Enhancing the resolution of spectral images from the advanced electro-optical system spectral imaging sensor,” Opt. Eng. 46, 057001 (2007).
[Crossref]

Campbell, P. K. E.

P. K. E. Campbell, E. M. Middleton, L. A. Corp, and M. S. Kim, “Contribution of chlorophyll fluorescence to the apparent vegetation reflectance,” Sci. Total Environ. 404, 433–439 (2008).
[Crossref]

Campos, J.

M. A. López-Álvarez, J. Hernández-Andrés, J. Romero, J. Campos, and A. Pons, “Calibrating the elements of a multispectral imaging system,” J. Imaging Sci. Technol. 53, 031102 (2009).
[Crossref]

Cao, D.

A. J. Zele and D. Cao, “Vision under mesopic and scotopic illumination,” Front. Psychol. 5, 1594, 1–15 (2015).
[Crossref]

Cao, D. C.

Cao, X.

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

Cardei, V. C.

V. C. Cardei and B. Funt, “Color correcting uncalibrated digital images,” J. Imaging Sci. Technol. 44, 288–378 (2000).

Caricato, V.

Carin, L.

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

Carney, P. S.

Chanussot, J.

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

Chen, Y.-W.

Cheung, V.

V. Cheung and S. Westland, “Methods for optimal color selection,” J. Imaging Sci. Technol. 50, 481–488 (2006).
[Crossref]

S. Westland, C. Ripamonti, and V. Cheung, Computational Colour Science Using Matlab, 2nd ed. (Wiley, 2012).

Y. Li, S. Westland, Q. Pan, and V. Cheung, “Methods to assess the relative number of discernible colors for displays,” in 22nd Color and Imaging Conference (Society for Imaging Science and Technology, 2014), pp. 151–154.

J. Morovic, V. Cheung, and P. Morovic, “Why we don’t know how many colors there are,” in CGIV 2012, 6th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2012), pp. 49–53.

Chiao, C.-C.

Chorro, E.

Claridge, E.

L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
[Crossref]

Clark, J. B.

J. B. Clark and G. R. Lister, “Photosynthetic action spectra of trees. II. The relationship of cuticle structure to the visible and ultraviolet spectral properties of needles from four coniferous species,” Plant Physiol. 55, 407–413 (1975).
[Crossref]

Coffey, V. C.

V. C. Coffey, “Hyperspectral imaging for safety and security,” Opt. Photon. News 26, 28–33 (2015).

Contreras, E. G.

Conway, B. R.

B. R. Conway, R. T. Eskew, P. R. Martin, and A. Stockman, “A tour of contemporary color vision research,” Vis. Res. 151, 2–6 (2018).
[Crossref]

Corp, L. A.

P. K. E. Campbell, E. M. Middleton, L. A. Corp, and M. S. Kim, “Contribution of chlorophyll fluorescence to the apparent vegetation reflectance,” Sci. Total Environ. 404, 433–439 (2008).
[Crossref]

Correa, C. V.

C. V. Correa, C. A. Hinojosa, G. R. Arce, and H. Arguello, “Multiple snapshot colored compressive spectral imager,” Opt. Eng. 56, 041309 (2016).
[Crossref]

Coudert, S.

D. G. Abdelsalam, M. Stanislas, and S. Coudert, “CCD or CMOS camera calibration using point spread function,” Proc. SPIE 9234, 92340Z (2014).
[Crossref]

Cover, T. M.

T. M. Cover and J. A. Thomas, Elements of Information Theory, 2nd ed. (Wiley, 2006).

Cowan, W.

W. Cowan, “Displays for vision research,” in Handbook of Optics. Volume III. Vision and Vision Optics, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 22.1–22.41.

Cronin, T. W.

Cui, G.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31, 320–330 (2006).
[Crossref]

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[Crossref]

Dacey, D. M.

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Dai, Q.-H.

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

Dangel, S.

G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing—definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006).
[Crossref]

Datla, R.

C. L. Wyatt, V. Privalsky, and R. Datla, Recommended practice: symbols, terms, units and uncertainty analysis for radiometric sensor calibration (National Institute of Standards and Technology, U.S. Department of Commerce Technology Administration, 1998).

Daub, C. O.

R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, “The mutual information: detecting and evaluating dependencies between variables,” Bioinformatics 18, S231–S240 (2002).
[Crossref]

de Fez, D.

Deeb, R.

R. Deeb, D. Muselet, M. Hebert, and A. Tremeau, “Interreflections in computer vision: a survey and an introduction to spectral infinite-bounce model,” J. Math. Imaging Vis. 60, 661–680 (2018).
[Crossref]

Delon, J.

E. Provenzi, J. Delon, Y. Gousseau, and B. Mazin, “On the second order spatiochromatic structure of natural images,” Vis. Res. 120, 22–38 (2016).
[Crossref]

Derrington, A. M.

A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. 357, 241–265 (1984).
[Crossref]

Dobigeon, N.

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

Doi, E.

E. Doi, T. Inue, T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Spatiochromatic receptive field properties derived from information-theoretic analyses of cone mosaic responses to natural scenes,” Neural Comput. 15, 397–417 (2003).
[Crossref]

Drew, M. S.

G. D. Finlayson, M. S. Drew, and B. V. Funt, “Spectral sharpening: sensor transformations for improved color constancy,” J. Opt. Soc. Am. A 11, 1553–1563 (1994).
[Crossref]

B. V. Funt and M. S. Drew, “Color space analysis of mutual illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1319–1326 (1993).
[Crossref]

B. V. Funt, M. S. Drew, and J. Ho, “Color constancy from mutual reflection,” Int. J. Comput. Vis. 6, 5–24 (1991).
[Crossref]

Du, Q.

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

Dusselaar, R.

Eaton, T.

P. Jerram, D. Burt, D. Morris, T. Eaton, and M. Fryer, “Design of image sensors for hyperspectral applications,” in Sensors, Systems, and Next-Generation Satellites XIII, R. Meynart, S. P. Neeck, and H. Shimoda, eds. (SPIE, 2009), pp. 74741E1.

Eckhard, J.

Eckhard, T.

Egidi, A.

Ekpenyong, N.

N. Ekpenyong, Hyperspectral Imaging: Calibration and Applications with Natural Scenes (School of Electrical and Electronic Engineering University of Manchester, 2013).

Ennis, R.

Eskew, R. T.

B. R. Conway, R. T. Eskew, P. R. Martin, and A. Stockman, “A tour of contemporary color vision research,” Vis. Res. 151, 2–6 (2018).
[Crossref]

Fach, C.

A. Stockman, L. T. Sharpe, and C. Fach, “The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches,” Vis. Res. 39, 2901–2927 (1999).
[Crossref]

Fairchild, M. D.

G. M. Johnson and M. D. Fairchild, “A top down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
[Crossref]

M. D. Fairchild, Color Appearance Models, 2nd ed. (Wiley, 2013).

Fairman, H. S.

H. S. Fairman, “An improved method for correcting radiance data for bandpass error,” Color Res. Appl. 35, 328–333 (2010).
[Crossref]

Fält, P.

L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
[Crossref]

Farrell, J. E.

X. Zhang, D. A. Silverstein, J. E. Farrell, and B. A. Wandell, “Color image quality metric S-CIELAB and its application on halftone texture visibility,” in IEEE COMPCON 97 (IEEE, 1997), pp. 44–48.

Farup, I.

A. M. Bakke, I. Farup, and J. Y. Hardeberg, “Evaluation of algorithms for the determination of color gamut boundaries,” J. Imaging Sci. Technol. 54, 050502 (2010).
[Crossref]

Felgueiras, P. E. R.

J. M. M. Linhares, P. E. R. Felgueiras, P. D. Pinto, and S. M. C. Nascimento, “Colour rendering of indoor lighting with CIE illuminants and white LEDs for normal and colour deficient observers,” Ophthalmic Physiolog. Opt. 30, 618–625 (2010).
[Crossref]

Feng, G.

Fider, N.

Fine, I.

Finlayson, G.

R. Bala, G. Finlayson, and C. Lee, “Computational color imaging,” in Handbook of Convex Optimization Methods in Imaging Science, V. Monga, ed. (Springer, 2017), pp. 43–70.

Finlayson, G. D.

Flinkman, M.

Flusser, J.

B. Zitová and J. Flusser, “Image registration methods: a survey,” Image Vis. Comput. 21, 977–1000 (2003).
[Crossref]

Foster, D. H.

D. H. Foster, “The Verriest lecture: color vision in an uncertain world,” J. Opt. Soc. Am. A 35, B192–B201 (2018).
[Crossref]

S. M. C. Nascimento, K. Amano, and D. H. Foster, “Spatial distributions of local illumination color in natural scenes,” Vis. Res. 120, 39–44 (2016).
[Crossref]

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Time-lapse ratios of cone excitations in natural scenes,” Vis. Res. 120, 45–60(2016).
[Crossref]

I. Marín-Franch and D. H. Foster, “Estimating Information from image colors: an application to digital cameras and natural scenes,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 78–91 (2013).
[Crossref]

G. Feng and D. H. Foster, “Predicting frequency of metamerism in natural scenes by entropy of colors,” J. Opt. Soc. Am. A 29, A200–A208 (2012).
[Crossref]

D. H. Foster, “Color constancy,” Vis. Res. 51, 674–700 (2011).
[Crossref]

I. Marín-Franch and D. H. Foster, “Number of perceptually distinct surface colors in natural scenes,” J. Vis. 10(9), 9 (2010).
[Crossref]

D. H. Foster, I. Marín-Franch, K. Amano, and S. M. C. Nascimento, “Approaching ideal observer efficiency in using color to retrieve information from natural scenes,” J. Opt. Soc. Am. A 26, B14–B24 (2009).
[Crossref]

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera and colored filters,” Color Res. Appl. 32, 352–360 (2007).
[Crossref]

D. H. Foster, K. Amano, S. M. C. Nascimento, and M. J. Foster, “Frequency of metamerism in natural scenes,” J. Opt. Soc. Am. A 23, 2359–2372 (2006).
[Crossref]

D. H. Foster and K. Żychaluk, “Is there a better non-parametric alternative to von Kries scaling?” in CGIV 2008, 4th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2008), pp. 41–44.

D. H. Foster, “Chromatic function of the cones,” in Encyclopedia of the Eye, D. A. Dartt, ed. (Academic, 2010), pp. 266–274.

Foster, M. J.

Fraser, C.

T. Luhmann, C. Fraser, and H.-G. Maas, “Sensor modelling and camera calibration for close-range photogrammetry,” ISPRS J. Photogramm. Remote Sens. 115, 37–46 (2016).
[Crossref]

Fryer, M.

P. Jerram, D. Burt, D. Morris, T. Eaton, and M. Fryer, “Design of image sensors for hyperspectral applications,” in Sensors, Systems, and Next-Generation Satellites XIII, R. Meynart, S. P. Neeck, and H. Shimoda, eds. (SPIE, 2009), pp. 74741E1.

Fukshansky, L.

J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. I. Introduction and the correction of leaf spectra for surface reflection,” Photochem. Photobiol. 51, 203–210 (1990).
[Crossref]

J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. II. The non-absorbed ray of the sieve effect and the mean optical pathlength in the remainder of the leaf,” Photochem. Photobiol. 51, 211–216 (1990).
[Crossref]

Funt, B.

K. Barnard and B. Funt, “Camera characterization for color research,” Color Res. Appl. 27, 152–163 (2002).
[Crossref]

V. C. Cardei and B. Funt, “Color correcting uncalibrated digital images,” J. Imaging Sci. Technol. 44, 288–378 (2000).

Funt, B. V.

G. D. Finlayson, M. S. Drew, and B. V. Funt, “Spectral sharpening: sensor transformations for improved color constancy,” J. Opt. Soc. Am. A 11, 1553–1563 (1994).
[Crossref]

B. V. Funt and M. S. Drew, “Color space analysis of mutual illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1319–1326 (1993).
[Crossref]

B. V. Funt, M. S. Drew, and J. Ho, “Color constancy from mutual reflection,” Int. J. Comput. Vis. 6, 5–24 (1991).
[Crossref]

Gader, P.

R. Heylen, M. Parente, and P. Gader, “A review of nonlinear hyperspectral unmixing methods,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 7, 1844–1868 (2014).
[Crossref]

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

Galvis, L.

Gamlin, P. D.

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Gamon, J. A.

D. A. Sims and J. A. Gamon, “Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages,” Remote Sens. Environ. 81, 337–354 (2002).
[Crossref]

Gao, J. B.

M. Paul, R. Xiao, J. B. Gao, and T. Bossomaier, “Reflectance prediction modelling for residual-based hyperspectral image coding,” PLoS ONE 11, e0161212 (2016).
[Crossref]

Gao, L.

L. Gao and L. V. Wang, “A review of snapshot multidimensional optical imaging: measuring photon tags in parallel,” Phys. Rep. 616, 1–37 (2016).
[Crossref]

Gat, N.

J. M. Lerner, N. Gat, and E. Wachman, “Approaches to spectral imaging hardware,” Curr. Protoc. Cytom. 53, 12–20 (2010).
[Crossref]

N. Gat, “Imaging spectroscopy using tunable filters: a review,” Proc. SPIE 4056, 50–64 (2000).
[Crossref]

Gegenfurtner, K. R.

Geladi, P.

J. Burger and P. Geladi, “Hyperspectral NIR image regression, part I: calibration and correction,” J. Chemom. 19, 355–363 (2005).
[Crossref]

P. Geladi, J. Burger, and T. Lestlander, “Hyperspectral imaging: calibration problems and solutions,” Chemom. Intell. Lab. Syst. 72, 209–217 (2004).
[Crossref]

Gevers, T.

A. Gijsenij, R. Lu, and T. Gevers, “Color constancy for multiple light sources,” IEEE Trans. Image Process. 21, 697–707 (2012).
[Crossref]

A. Gijsenij, T. Gevers, and J. van de Weijer, “Computational color constancy: survey and experiments,” IEEE Trans. Image Process. 20, 2475–2489 (2011).
[Crossref]

Gijsenij, A.

A. Gijsenij, R. Lu, and T. Gevers, “Color constancy for multiple light sources,” IEEE Trans. Image Process. 21, 697–707 (2012).
[Crossref]

A. Gijsenij, T. Gevers, and J. van de Weijer, “Computational color constancy: survey and experiments,” IEEE Trans. Image Process. 20, 2475–2489 (2011).
[Crossref]

Gilabert, E.

Ginsberg, I. W.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, Geometrical considerations and nomenclature for reflectance (Institute for Basic Standards/National Bureau of Standards, 1997).

Goda, M. E.

T. F. Blake, S. C. Cain, and M. E. Goda, “Enhancing the resolution of spectral images from the advanced electro-optical system spectral imaging sensor,” Opt. Eng. 46, 057001 (2007).
[Crossref]

Goldstein, R.

Gori, F.

Goria, M. N.

M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. Novi Inverardi, “A new class of random vector entropy estimators and its applications in testing statistical hypotheses,” J. Nonparametr. Stat. 17, 277–297 (2005).
[Crossref]

Gottschalk, A.

G. Buchsbaum and A. Gottschalk, “Trichromacy, opponent colours coding and optimum colour information transmission in the retina,” Proc. R. Soc. London B 220, 89–113 (1983).
[Crossref]

Gousseau, Y.

E. Provenzi, J. Delon, Y. Gousseau, and B. Mazin, “On the second order spatiochromatic structure of natural images,” Vis. Res. 120, 22–38 (2016).
[Crossref]

Gouton, P.

A. Mansouri, F. S. Marzani, and P. Gouton, “Development of a protocol for CCD calibration: application to a multispectral imaging system,” Int. J. Robot. Autom. 20, 94–100 (2005).

X.-B. Wang, P. J. Green, J.-B. Thomas, J. Y. Hardeberg, and P. Gouton, “Evaluation of the colorimetric performance of single-sensor image acquisition systems employing colour and multispectral filter array,” in Computational Color Imaging, CCIW, A. Trémeau, R. Schettini, and S. Tominaga, eds. (Springer, 2015), pp. 181–191.

Green, P. J.

X.-B. Wang, P. J. Green, J.-B. Thomas, J. Y. Hardeberg, and P. Gouton, “Evaluation of the colorimetric performance of single-sensor image acquisition systems employing colour and multispectral filter array,” in Computational Color Imaging, CCIW, A. Trémeau, R. Schettini, and S. Tominaga, eds. (Springer, 2015), pp. 181–191.

Grendar, M.

M. Grendar, “Entropy and effective support size,” Entropy 8, 169–174 (2006).
[Crossref]

Gu, L.

L. Gu, C. P. Huynh, and A. Robles-Kelly, “Segmentation and estimation of spatially varying illumination,” IEEE Trans. Image Process. 23, 3478–3489 (2014).
[Crossref]

Günther-Kohfahl, S.

E. Buhr, S. Günther-Kohfahl, and U. Neitzel, “Simple method for modulation transfer function determination of digital imaging detectors from edge images,” Proc. SPIE 5030, 877–884 (2003).
[Crossref]

Guo, F.

Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
[Crossref]

Hagen, N.

N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013).
[Crossref]

Hakala, T.

Hardeberg, J. Y.

H. A. Khan, S. Mihoubi, B. Mathon, J.-B. Thomas, and J. Y. Hardeberg, “HyTexiLa: high resolution visible and near infrared hyperspectral texture images,” Sensors 18, 2045 (2018).
[Crossref]

H. A. Khan, J.-B. Thomas, J. Y. Hardeberg, and O. Laligant, “Illuminant estimation in multispectral imaging,” J. Opt. Soc. Am. A 34, 1085–1098 (2017).
[Crossref]

S. Le Moan, A. Mansouri, Y. Voisin, and J. Y. Hardeberg, “A constrained band selection method based on information measures for spectral image color visualization,” IEEE Trans. Geosci. Remote Sens. 49, 5104–5115 (2011).
[Crossref]

A. M. Bakke, I. Farup, and J. Y. Hardeberg, “Evaluation of algorithms for the determination of color gamut boundaries,” J. Imaging Sci. Technol. 54, 050502 (2010).
[Crossref]

J. Y. Hardeberg, F. Schmitt, and H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41, 2532–2548 (2002).
[Crossref]

X.-B. Wang, P. J. Green, J.-B. Thomas, J. Y. Hardeberg, and P. Gouton, “Evaluation of the colorimetric performance of single-sensor image acquisition systems employing colour and multispectral filter array,” in Computational Color Imaging, CCIW, A. Trémeau, R. Schettini, and S. Tominaga, eds. (Springer, 2015), pp. 181–191.

Hauta-Kasari, M.

L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
[Crossref]

M. Flinkman, H. Laamanen, P. Vahimaa, and M. Hauta-Kasari, “Number of colors generated by smooth nonfluorescent reflectance spectra,” J. Opt. Soc. Am. A 29, 2566–2575 (2012).
[Crossref]

Hawken, M. J.

R. Shapley and M. J. Hawken, “Color in the cortex: single- and double-opponent cells,” Vision Res. 51, 701–717 (2011).
[Crossref]

He, X.

Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
[Crossref]

Hebert, M.

R. Deeb, D. Muselet, M. Hebert, and A. Tremeau, “Interreflections in computer vision: a survey and an introduction to spectral infinite-bounce model,” J. Math. Imaging Vis. 60, 661–680 (2018).
[Crossref]

Helling, S.

S. Helling, “Improvement of multispectral image capture by compensating for stray light,” in CGIV 2006, 3rd European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2006), pp. 458–462.

Hernández-Andrés, J.

Heylen, R.

R. Heylen, M. Parente, and P. Gader, “A review of nonlinear hyperspectral unmixing methods,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 7, 1844–1868 (2014).
[Crossref]

Hill, B.

B. Hill, T. Roger, and F. W. Vorhagen, “Comparative analysis of the quantization of color spaces on the basis of the CIELAB color-difference formula,” ACM Trans. Graph. 16, 109–154 (1997).
[Crossref]

Hinojosa, C. A.

C. V. Correa, C. A. Hinojosa, G. R. Arce, and H. Arguello, “Multiple snapshot colored compressive spectral imager,” Opt. Eng. 56, 041309 (2016).
[Crossref]

Hirai, K.

Ho, J.

B. V. Funt, M. S. Drew, and J. Ho, “Color constancy from mutual reflection,” Int. J. Comput. Vis. 6, 5–24 (1991).
[Crossref]

Horiuchi, T.

Howell, S. B.

S. B. Howell, Handbook of CCD Astronomy, 2nd ed., Cambridge Observing Handbooks for Research Astronomers (Cambridge University, 2006).

Hsia, J. J.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, Geometrical considerations and nomenclature for reflectance (Institute for Basic Standards/National Bureau of Standards, 1997).

Huang, M.

L.-L. Qian, Q.-B. Lü, M. Huang, Q.-S. Cai, and B. Xiang-li, “Effect of keystone on coded aperture spectral imaging,” Optik 127, 686–689 (2016).
[Crossref]

Huertas, R.

Hunt, R. W. G.

C. Li, M. R. Luo, B. Rigg, and R. W. G. Hunt, “CMC 2000 chromatic adaptation transform: CMCCAT2000,” Color Res. Appl. 27, 49–58 (2002).
[Crossref]

M. R. Luo and R. W. G. Hunt, “A chromatic adaptation transform and a colour inconstancy index,” Color Res. Appl. 23, 154–158 (1998).
[Crossref]

Hurlbert, A.

Huynh, C. P.

L. Gu, C. P. Huynh, and A. Robles-Kelly, “Segmentation and estimation of spatially varying illumination,” IEEE Trans. Image Process. 23, 3478–3489 (2014).
[Crossref]

Imai, F. H.

F. H. Imai and R. S. Berns, “Spectral estimation using trichromatic digital cameras,” in International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42–49.

F. H. Imai, M. R. Rosen, and R. S. Berns, “Comparison of spectrally narrow-band capture versus wide-band with a priori sample analysis for spectral reflectance estimation,” in Eighth Color Imaging Conference: Color Science and Engineering: Systems, Technologies and Applications (Society for Imaging Science and Technology, 2000), pp. 234–241.

Inue, T.

E. Doi, T. Inue, T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Spatiochromatic receptive field properties derived from information-theoretic analyses of cone mosaic responses to natural scenes,” Neural Comput. 15, 397–417 (2003).
[Crossref]

Jacobson, R. E.

M. R. Pointer, G. G. Attridge, and R. E. Jacobson, “Practical camera characterization for colour measurement,” Imaging Sci. J. 49, 63–80 (2001).
[Crossref]

Jain, S. C.

J. R. Miller, S. C. Jain, N. T. O’Neill, W. R. McNeil, and K. P. B. Thomson, “Interpretation of airborne spectral reflectance measurements over Georgian Bay,” Remote Sens. Environ. 6, 183–200 (1977).
[Crossref]

Janesick, J. R.

J. R. Janesick, Photon Transfer DN → λ (SPIE, 2007).

Jansson, P. A.

P. A. Jansson and R. P. Breault, “Correcting color-measurement error caused by stray light in image scanners,” in Sixth Color and Imaging Conference: Color Science, Systems, and Applications (Society for Imaging Science and Technology, 1998), pp. 69–73.

Jerram, P.

P. Jerram, D. Burt, D. Morris, T. Eaton, and M. Fryer, “Design of image sensors for hyperspectral applications,” in Sensors, Systems, and Next-Generation Satellites XIII, R. Meynart, S. P. Neeck, and H. Shimoda, eds. (SPIE, 2009), pp. 74741E1.

João, C. A. R.

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

Johnson, G. M.

G. M. Johnson and M. D. Fairchild, “A top down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
[Crossref]

E. Reinhard, E. A. Khan, A. O. Akyüz, and G. M. Johnson, Color Imaging: Fundamentals and Applications (A. K. Peters, 2008).

Johnson, R. B.

R. Kingslake and R. B. Johnson, Lens Design Fundamentals, 2nd ed. (Academic/SPIE, 2010).

Kaasalainen, S.

Karantzalos, K.

M. Vakalopoulou and K. Karantzalos, “Automatic descriptor-based co-registration of frame hyperspectral data,” Remote Sens. 6, 3409–3426 (2014).
[Crossref]

Kato, K.

Khan, E. A.

E. Reinhard, E. A. Khan, A. O. Akyüz, and G. M. Johnson, Color Imaging: Fundamentals and Applications (A. K. Peters, 2008).

Khan, H. A.

H. A. Khan, S. Mihoubi, B. Mathon, J.-B. Thomas, and J. Y. Hardeberg, “HyTexiLa: high resolution visible and near infrared hyperspectral texture images,” Sensors 18, 2045 (2018).
[Crossref]

H. A. Khan, J.-B. Thomas, J. Y. Hardeberg, and O. Laligant, “Illuminant estimation in multispectral imaging,” J. Opt. Soc. Am. A 34, 1085–1098 (2017).
[Crossref]

Kim, M. S.

P. K. E. Campbell, E. M. Middleton, L. A. Corp, and M. S. Kim, “Contribution of chlorophyll fluorescence to the apparent vegetation reflectance,” Sci. Total Environ. 404, 433–439 (2008).
[Crossref]

Kingslake, R.

R. Kingslake and R. B. Johnson, Lens Design Fundamentals, 2nd ed. (Academic/SPIE, 2010).

Klir, G. J.

G. J. Klir, Uncertainty and Information: Foundations of Generalized Information Theory (Wiley, 2006).

Komarova, N. L.

Kozachenko, L. F.

L. F. Kozachenko and N. N. Leonenko, “Sample estimate of the entropy of a random vector,” Probl. Inf. Transm. 23, 95–101(1987).

Krauskopf, J.

A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. 357, 241–265 (1984).
[Crossref]

Kudenov, M. W.

N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013).
[Crossref]

Kurths, J.

R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, “The mutual information: detecting and evaluating dependencies between variables,” Bioinformatics 18, S231–S240 (2002).
[Crossref]

Kurz, T. H.

T. H. Kurz and S. J. Buckley, “A review of hyperspectral imaging in close range applications,” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XLI-B5, 865–870 (2016).
[Crossref]

Laaksonen, L.

L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
[Crossref]

Laamanen, H.

Laligant, O.

Lamb, T. D.

T. D. Lamb, “Why rods and cones?” Eye 30, 179–185 (2016).
[Crossref]

Lapidoth, A.

A. Lapidoth, “Nearest neighbor decoding for additive non-Gaussian noise channels,” IEEE Trans. Inf. Theory 42, 1520–1529 (1996).
[Crossref]

Le Moan, S.

S. Le Moan and P. Urban, “Image-difference prediction: from color to spectral,” IEEE Trans. Image Process. 23, 2058–2068 (2014).
[Crossref]

S. Le Moan, A. Mansouri, Y. Voisin, and J. Y. Hardeberg, “A constrained band selection method based on information measures for spectral image color visualization,” IEEE Trans. Geosci. Remote Sens. 49, 5104–5115 (2011).
[Crossref]

Lee, C.

R. Bala, G. Finlayson, and C. Lee, “Computational color imaging,” in Handbook of Convex Optimization Methods in Imaging Science, V. Monga, ed. (Springer, 2017), pp. 43–70.

Lee, D.

D. Lee, Nature’s Palette: The Science of Plant Color (University of Chicago, 2007).

Lee, T.-W.

E. Doi, T. Inue, T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Spatiochromatic receptive field properties derived from information-theoretic analyses of cone mosaic responses to natural scenes,” Neural Comput. 15, 397–417 (2003).
[Crossref]

T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Color opponency is an efficient representation of spectral properties in natural scenes,” Vis. Res. 42, 2095–2103 (2002).
[Crossref]

Legge, G. E.

Lennie, P.

A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. 357, 241–265 (1984).
[Crossref]

Lensu, L.

L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
[Crossref]

Leonenko, N. N.

M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. Novi Inverardi, “A new class of random vector entropy estimators and its applications in testing statistical hypotheses,” J. Nonparametr. Stat. 17, 277–297 (2005).
[Crossref]

L. F. Kozachenko and N. N. Leonenko, “Sample estimate of the entropy of a random vector,” Probl. Inf. Transm. 23, 95–101(1987).

Lerner, J. M.

J. M. Lerner, N. Gat, and E. Wachman, “Approaches to spectral imaging hardware,” Curr. Protoc. Cytom. 53, 12–20 (2010).
[Crossref]

Lestlander, T.

P. Geladi, J. Burger, and T. Lestlander, “Hyperspectral imaging: calibration problems and solutions,” Chemom. Intell. Lab. Syst. 72, 209–217 (2004).
[Crossref]

Lewis, A.

A. Lewis and L. Zhaoping, “Are cone sensitivities determined by natural color statistics?” J. Vis. 6 (3), 285–302 (2006).
[Crossref]

Li, C.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31, 320–330 (2006).
[Crossref]

C. Li, M. R. Luo, B. Rigg, and R. W. G. Hunt, “CMC 2000 chromatic adaptation transform: CMCCAT2000,” Color Res. Appl. 27, 49–58 (2002).
[Crossref]

Li, Q.

Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
[Crossref]

Li, Y.

Y. Li, S. Westland, Q. Pan, and V. Cheung, “Methods to assess the relative number of discernible colors for displays,” in 22nd Color and Imaging Conference (Society for Imaging Science and Technology, 2014), pp. 151–154.

Li, Z.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

Liang, H.

H. Liang, “Advances in multispectral and hyperspectral imaging for archaeology and art conservation,” Appl. Phys. A 106, 309–323 (2012).
[Crossref]

Liao, H.-W.

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Lichtenthaler, H. K.

H. K. Lichtenthaler and U. Rinderle, “The role of chlorophyll fluorescence in the detection of stress conditions in plants,” CRC Crit. Rev. Anal. Chem. 19, S29–S85 (1988).
[Crossref]

Limperis, T.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, Geometrical considerations and nomenclature for reflectance (Institute for Basic Standards/National Bureau of Standards, 1997).

Lin, S.

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

Lin, X.

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

Ling, Y.

Linhares, J. M. M.

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

C. Montagner, J. M. M. Linhares, M. Vilarigues, and S. M. C. Nascimento, “Statistics of colors in paintings and natural scenes,” J. Opt. Soc. Am. A 33, A170–A177 (2016).
[Crossref]

J. M. M. Linhares, P. E. R. Felgueiras, P. D. Pinto, and S. M. C. Nascimento, “Colour rendering of indoor lighting with CIE illuminants and white LEDs for normal and colour deficient observers,” Ophthalmic Physiolog. Opt. 30, 618–625 (2010).
[Crossref]

J. M. M. Linhares, P. D. A. Pinto, and S. M. C. Nascimento, “Color rendering of art paintings under CIE illuminants for normal and color deficient observers,” J. Opt. Soc. Am. A 26, 1668–1677 (2009).
[Crossref]

J. M. M. Linhares, P. D. Pinto, and S. M. C. Nascimento, “The number of discernible colors in natural scenes,” J. Opt. Soc. Am. A 25, 2918–2924 (2008).
[Crossref]

Lister, G. R.

J. B. Clark and G. R. Lister, “Photosynthetic action spectra of trees. II. The relationship of cuticle structure to the visible and ultraviolet spectral properties of needles from four coniferous species,” Plant Physiol. 55, 407–413 (1975).
[Crossref]

Liu, H.

Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
[Crossref]

López-Álvarez, M. A.

M. A. López-Álvarez, J. Hernández-Andrés, J. Romero, J. Campos, and A. Pons, “Calibrating the elements of a multispectral imaging system,” J. Imaging Sci. Technol. 53, 031102 (2009).
[Crossref]

Love, R. C.

R. C. Love, Surface Reflection Model Estimation from Naturally Illuminated Image Sequences (School of Computer Studies, University of Leeds, 1997).

Lu, R.

A. Gijsenij, R. Lu, and T. Gevers, “Color constancy for multiple light sources,” IEEE Trans. Image Process. 21, 697–707 (2012).
[Crossref]

Lü, Q.-B.

L.-L. Qian, Q.-B. Lü, M. Huang, Q.-S. Cai, and B. Xiang-li, “Effect of keystone on coded aperture spectral imaging,” Optik 127, 686–689 (2016).
[Crossref]

Luhmann, T.

T. Luhmann, C. Fraser, and H.-G. Maas, “Sensor modelling and camera calibration for close-range photogrammetry,” ISPRS J. Photogramm. Remote Sens. 115, 37–46 (2016).
[Crossref]

Luo, M. R.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31, 320–330 (2006).
[Crossref]

C. Li, M. R. Luo, B. Rigg, and R. W. G. Hunt, “CMC 2000 chromatic adaptation transform: CMCCAT2000,” Color Res. Appl. 27, 49–58 (2002).
[Crossref]

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[Crossref]

M. R. Luo and R. W. G. Hunt, “A chromatic adaptation transform and a colour inconstancy index,” Color Res. Appl. 23, 154–158 (1998).
[Crossref]

Maas, H.-G.

T. Luhmann, C. Fraser, and H.-G. Maas, “Sensor modelling and camera calibration for close-range photogrammetry,” ISPRS J. Photogramm. Remote Sens. 115, 37–46 (2016).
[Crossref]

MacAdam, D. L.

MacKay, D. J. C.

D. J. C. MacKay, Information Theory, Inference, and Learning Algorithms (Cambridge University, 2003).

MacLeod, D. I. A.

Maloney, L. T.

D. H. Brainard and L. T. Maloney, “Surface color perception and equivalent illumination models,” J. Vis. 11(5), 1 (2011).
[Crossref]

Mansouri, A.

S. Le Moan, A. Mansouri, Y. Voisin, and J. Y. Hardeberg, “A constrained band selection method based on information measures for spectral image color visualization,” IEEE Trans. Geosci. Remote Sens. 49, 5104–5115 (2011).
[Crossref]

A. Mansouri, F. S. Marzani, and P. Gouton, “Development of a protocol for CCD calibration: application to a multispectral imaging system,” Int. J. Robot. Autom. 20, 94–100 (2005).

Marín-Franch, I.

I. Marín-Franch and D. H. Foster, “Estimating Information from image colors: an application to digital cameras and natural scenes,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 78–91 (2013).
[Crossref]

I. Marín-Franch and D. H. Foster, “Number of perceptually distinct surface colors in natural scenes,” J. Vis. 10(9), 9 (2010).
[Crossref]

D. H. Foster, I. Marín-Franch, K. Amano, and S. M. C. Nascimento, “Approaching ideal observer efficiency in using color to retrieve information from natural scenes,” J. Opt. Soc. Am. A 26, B14–B24 (2009).
[Crossref]

Martin, P. R.

B. R. Conway, R. T. Eskew, P. R. Martin, and A. Stockman, “A tour of contemporary color vision research,” Vis. Res. 151, 2–6 (2018).
[Crossref]

S. K. Shevell and P. R. Martin, “Color opponency: tutorial,” J. Opt. Soc. Am. A 34, 1099–1108 (2017).
[Crossref]

Martínez-Verdú, F.

Martonchik, J. V.

G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing—definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006).
[Crossref]

Marzani, F. S.

A. Mansouri, F. S. Marzani, and P. Gouton, “Development of a protocol for CCD calibration: application to a multispectral imaging system,” Int. J. Robot. Autom. 20, 94–100 (2005).

Mathon, B.

H. A. Khan, S. Mihoubi, B. Mathon, J.-B. Thomas, and J. Y. Hardeberg, “HyTexiLa: high resolution visible and near infrared hyperspectral texture images,” Sensors 18, 2045 (2018).
[Crossref]

Mazin, B.

E. Provenzi, J. Delon, Y. Gousseau, and B. Mazin, “On the second order spatiochromatic structure of natural images,” Vis. Res. 120, 22–38 (2016).
[Crossref]

McClendon, J. H.

J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. I. Introduction and the correction of leaf spectra for surface reflection,” Photochem. Photobiol. 51, 203–210 (1990).
[Crossref]

J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. II. The non-absorbed ray of the sieve effect and the mean optical pathlength in the remainder of the leaf,” Photochem. Photobiol. 51, 211–216 (1990).
[Crossref]

J. H. McClendon, “The micro-optics of leaves. I. Patterns of reflection from the epidermis,” Am. J. Bot. 71, 1391–1397 (1984).
[Crossref]

McNeil, W. R.

J. R. Miller, S. C. Jain, N. T. O’Neill, W. R. McNeil, and K. P. B. Thomson, “Interpretation of airborne spectral reflectance measurements over Georgian Bay,” Remote Sens. Environ. 6, 183–200 (1977).
[Crossref]

Melgosa, M.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

M. Melgosa, R. Huertas, and R. S. Berns, “Performance of recent advanced color-difference formulas using the standardized residual sum of squares index,” J. Opt. Soc. Am. A 25, 1828–1834 (2008).
[Crossref]

Mergel, V. V.

M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. Novi Inverardi, “A new class of random vector entropy estimators and its applications in testing statistical hypotheses,” J. Nonparametr. Stat. 17, 277–297 (2005).
[Crossref]

Middleton, E. M.

P. K. E. Campbell, E. M. Middleton, L. A. Corp, and M. S. Kim, “Contribution of chlorophyll fluorescence to the apparent vegetation reflectance,” Sci. Total Environ. 404, 433–439 (2008).
[Crossref]

Mihoubi, S.

H. A. Khan, S. Mihoubi, B. Mathon, J.-B. Thomas, and J. Y. Hardeberg, “HyTexiLa: high resolution visible and near infrared hyperspectral texture images,” Sensors 18, 2045 (2018).
[Crossref]

Miller, J. R.

J. R. Miller, S. C. Jain, N. T. O’Neill, W. R. McNeil, and K. P. B. Thomson, “Interpretation of airborne spectral reflectance measurements over Georgian Bay,” Remote Sens. Environ. 6, 183–200 (1977).
[Crossref]

Mokrzycki, W. S.

W. S. Mokrzycki and M. Tatol, “Colour difference ΔE–a survey,” Mach. Graph. Vis. 20, 383–411 (2011).

Montagner, C.

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

C. Montagner, J. M. M. Linhares, M. Vilarigues, and S. M. C. Nascimento, “Statistics of colors in paintings and natural scenes,” J. Opt. Soc. Am. A 33, A170–A177 (2016).
[Crossref]

Moorehead, I. R.

Morimoto, T.

Morovic, J.

P.-L. Sun and J. Morovic, “Inter-relating colour difference metrics,” in Tenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications (Society for Imaging Science and Technology, 2002), pp. 55–60.

J. Morovic, V. Cheung, and P. Morovic, “Why we don’t know how many colors there are,” in CGIV 2012, 6th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2012), pp. 49–53.

J. Morovič, Color Gamut Mapping (Wiley, 2008).

Morovic, P.

J. Morovic, V. Cheung, and P. Morovic, “Why we don’t know how many colors there are,” in CGIV 2012, 6th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2012), pp. 49–53.

Morris, D.

P. Jerram, D. Burt, D. Morris, T. Eaton, and M. Fryer, “Design of image sensors for hyperspectral applications,” in Sensors, Systems, and Next-Generation Satellites XIII, R. Meynart, S. P. Neeck, and H. Shimoda, eds. (SPIE, 2009), pp. 74741E1.

Mount, D. M.

S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, “An optimal algorithm for approximate nearest neighbor searching in fixed dimensions,” J. ACM 45, 891–923 (1998).
[Crossref]

D. M. Mount and S. Arya, “ANN: a library for approximate nearest neighbor searching, version 1.1.2,” (University of Maryland, 2010).

Muselet, D.

R. Deeb, D. Muselet, M. Hebert, and A. Tremeau, “Interreflections in computer vision: a survey and an introduction to spectral infinite-bounce model,” J. Math. Imaging Vis. 60, 661–680 (2018).
[Crossref]

Nascimento, S. M. C.

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Time-lapse ratios of cone excitations in natural scenes,” Vis. Res. 120, 45–60(2016).
[Crossref]

S. M. C. Nascimento, K. Amano, and D. H. Foster, “Spatial distributions of local illumination color in natural scenes,” Vis. Res. 120, 39–44 (2016).
[Crossref]

C. Montagner, J. M. M. Linhares, M. Vilarigues, and S. M. C. Nascimento, “Statistics of colors in paintings and natural scenes,” J. Opt. Soc. Am. A 33, A170–A177 (2016).
[Crossref]

J. M. M. Linhares, P. E. R. Felgueiras, P. D. Pinto, and S. M. C. Nascimento, “Colour rendering of indoor lighting with CIE illuminants and white LEDs for normal and colour deficient observers,” Ophthalmic Physiolog. Opt. 30, 618–625 (2010).
[Crossref]

D. H. Foster, I. Marín-Franch, K. Amano, and S. M. C. Nascimento, “Approaching ideal observer efficiency in using color to retrieve information from natural scenes,” J. Opt. Soc. Am. A 26, B14–B24 (2009).
[Crossref]

J. M. M. Linhares, P. D. A. Pinto, and S. M. C. Nascimento, “Color rendering of art paintings under CIE illuminants for normal and color deficient observers,” J. Opt. Soc. Am. A 26, 1668–1677 (2009).
[Crossref]

J. M. M. Linhares, P. D. Pinto, and S. M. C. Nascimento, “The number of discernible colors in natural scenes,” J. Opt. Soc. Am. A 25, 2918–2924 (2008).
[Crossref]

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera and colored filters,” Color Res. Appl. 32, 352–360 (2007).
[Crossref]

D. H. Foster, K. Amano, S. M. C. Nascimento, and M. J. Foster, “Frequency of metamerism in natural scenes,” J. Opt. Soc. Am. A 23, 2359–2372 (2006).
[Crossref]

Neitzel, U.

E. Buhr, S. Günther-Kohfahl, and U. Neitzel, “Simple method for modulation transfer function determination of digital imaging detectors from edge images,” Proc. SPIE 5030, 877–884 (2003).
[Crossref]

Netanyahu, N. S.

S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, “An optimal algorithm for approximate nearest neighbor searching in fixed dimensions,” J. ACM 45, 891–923 (1998).
[Crossref]

Nicodemus, F. E.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, Geometrical considerations and nomenclature for reflectance (Institute for Basic Standards/National Bureau of Standards, 1997).

Nieves, J. L.

Novi Inverardi, P. L.

M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. Novi Inverardi, “A new class of random vector entropy estimators and its applications in testing statistical hypotheses,” J. Nonparametr. Stat. 17, 277–297 (2005).
[Crossref]

O’Neill, N. T.

J. R. Miller, S. C. Jain, N. T. O’Neill, W. R. McNeil, and K. P. B. Thomson, “Interpretation of airborne spectral reflectance measurements over Georgian Bay,” Remote Sens. Environ. 6, 183–200 (1977).
[Crossref]

Painter, T. H.

G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing—definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006).
[Crossref]

Palmer, J. M.

J. M. Palmer, “Radiometry and photometry: units and conversions,” in Handbook of Optics, Volume II, Design, Fabrication, and Testing; Sources and Detectors; Radiometry and Photometry, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 36.1–36.19.

Pan, Q.

Y. Li, S. Westland, Q. Pan, and V. Cheung, “Methods to assess the relative number of discernible colors for displays,” in 22nd Color and Imaging Conference (Society for Imaging Science and Technology, 2014), pp. 151–154.

Parente, M.

R. Heylen, M. Parente, and P. Gader, “A review of nonlinear hyperspectral unmixing methods,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 7, 1844–1868 (2014).
[Crossref]

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

Parraga, C. A.

J. Roca-Vila, C. A. Parraga, and M. Vanrell, “Chromatic settings and the structural color constancy index,” J. Vis. 13 (4), 3 (2013).
[Crossref]

Párraga, C. A.

Paul, M.

R. Dusselaar and M. Paul, “Hyperspectral image compression approaches: opportunities, challenges, and future directions: discussion,” J. Opt. Soc. Am. A 34, 2170–2180 (2017).
[Crossref]

M. Paul, R. Xiao, J. B. Gao, and T. Bossomaier, “Reflectance prediction modelling for residual-based hyperspectral image coding,” PLoS ONE 11, e0161212 (2016).
[Crossref]

Perales, E.

Peterson, B. B.

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Pinto, P. D.

J. M. M. Linhares, P. E. R. Felgueiras, P. D. Pinto, and S. M. C. Nascimento, “Colour rendering of indoor lighting with CIE illuminants and white LEDs for normal and colour deficient observers,” Ophthalmic Physiolog. Opt. 30, 618–625 (2010).
[Crossref]

J. M. M. Linhares, P. D. Pinto, and S. M. C. Nascimento, “The number of discernible colors in natural scenes,” J. Opt. Soc. Am. A 25, 2918–2924 (2008).
[Crossref]

Pinto, P. D. A.

Pisani, M.

Plaza, A.

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

Pointer, M.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

Pointer, M. R.

M. R. Pointer, G. G. Attridge, and R. E. Jacobson, “Practical camera characterization for colour measurement,” Imaging Sci. J. 49, 63–80 (2001).
[Crossref]

M. R. Pointer and G. G. Attridge, “The number of discernible colours,” Color Res. Appl. 23, 52–54 (1998).
[Crossref]

Pokorny, J.

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Pons, A.

M. A. López-Álvarez, J. Hernández-Andrés, J. Romero, J. Campos, and A. Pons, “Calibrating the elements of a multispectral imaging system,” J. Imaging Sci. Technol. 53, 031102 (2009).
[Crossref]

Prasad, D. K.

Pratt, W. K.

W. K. Pratt, Digital Image Processing, 4th ed. (Wiley, 2007).

Privalsky, V.

C. L. Wyatt, V. Privalsky, and R. Datla, Recommended practice: symbols, terms, units and uncertainty analysis for radiometric sensor calibration (National Institute of Standards and Technology, U.S. Department of Commerce Technology Administration, 1998).

Provenzi, E.

E. Provenzi, J. Delon, Y. Gousseau, and B. Mazin, “On the second order spatiochromatic structure of natural images,” Vis. Res. 120, 22–38 (2016).
[Crossref]

Qian, L.-L.

L.-L. Qian, Q.-B. Lü, M. Huang, Q.-S. Cai, and B. Xiang-li, “Effect of keystone on coded aperture spectral imaging,” Optik 127, 686–689 (2016).
[Crossref]

Ramachandran, V.

K. S. Babu, V. Ramachandran, K. K. Thyagharajan, and G. Santhosh, “Hyperspectral image compression algorithms—a review,” in International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES), L. P. Suresh, S. S. Dash, and B. K. Panigrahi, eds. (Springer, 2015), Vol. 2, pp. 127–138.

Reeves, A.

Reinhard, E.

E. Reinhard, E. A. Khan, A. O. Akyüz, and G. M. Johnson, Color Imaging: Fundamentals and Applications (A. K. Peters, 2008).

Richmond, J. C.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, Geometrical considerations and nomenclature for reflectance (Institute for Basic Standards/National Bureau of Standards, 1997).

Rigg, B.

C. Li, M. R. Luo, B. Rigg, and R. W. G. Hunt, “CMC 2000 chromatic adaptation transform: CMCCAT2000,” Color Res. Appl. 27, 49–58 (2002).
[Crossref]

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[Crossref]

Rinderle, U.

H. K. Lichtenthaler and U. Rinderle, “The role of chlorophyll fluorescence in the detection of stress conditions in plants,” CRC Crit. Rev. Anal. Chem. 19, S29–S85 (1988).
[Crossref]

Ripamonti, C.

S. Westland, C. Ripamonti, and V. Cheung, Computational Colour Science Using Matlab, 2nd ed. (Wiley, 2012).

Robinson, F. R.

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Robles-Kelly, A.

L. Gu, C. P. Huynh, and A. Robles-Kelly, “Segmentation and estimation of spatially varying illumination,” IEEE Trans. Image Process. 23, 3478–3489 (2014).
[Crossref]

Roca-Vila, J.

J. Roca-Vila, C. A. Parraga, and M. Vanrell, “Chromatic settings and the structural color constancy index,” J. Vis. 13 (4), 3 (2013).
[Crossref]

Roger, T.

B. Hill, T. Roger, and F. W. Vorhagen, “Comparative analysis of the quantization of color spaces on the basis of the CIELAB color-difference formula,” ACM Trans. Graph. 16, 109–154 (1997).
[Crossref]

Romero, J.

J. L. Nieves and J. Romero, “Heuristic analysis influence of saliency in the color diversity of natural images,” Color Res. Appl. 43, 713–725 (2018).
[Crossref]

M. A. López-Álvarez, J. Hernández-Andrés, J. Romero, J. Campos, and A. Pons, “Calibrating the elements of a multispectral imaging system,” J. Imaging Sci. Technol. 53, 031102 (2009).
[Crossref]

J. L. Nieves, E. M. Valero, J. Hernández-Andrés, and J. Romero, “Recovering fluorescent spectra with an RGB digital camera and color filters using different matrix factorizations,” Appl. Opt. 46, 4144–4154 (2007).
[Crossref]

J. Hernández-Andrés, J. Romero, and J. L. Nieves, “Color and spectral analysis of daylight in southern Europe,” J. Opt. Soc. Am. A 18, 1325–1335 (2001).
[Crossref]

Rosen, M. R.

F. H. Imai, M. R. Rosen, and R. S. Berns, “Comparison of spectrally narrow-band capture versus wide-band with a priori sample analysis for spectral reflectance estimation,” in Eighth Color Imaging Conference: Color Science and Engineering: Systems, Technologies and Applications (Society for Imaging Science and Technology, 2000), pp. 234–241.

Ruderman, D. L.

Salvi, J.

J. Salvi, X. Armangué, and J. Batlle, “A comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recogn. 35, 1617–1635 (2002).
[Crossref]

Santhosh, G.

K. S. Babu, V. Ramachandran, K. K. Thyagharajan, and G. Santhosh, “Hyperspectral image compression algorithms—a review,” in International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES), L. P. Suresh, S. S. Dash, and B. K. Panigrahi, eds. (Springer, 2015), Vol. 2, pp. 127–138.

Schaepman, M. E.

G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing—definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006).
[Crossref]

Schaepman-Strub, G.

G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing—definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006).
[Crossref]

Schiller, F.

Schirillo, J.

Schmitt, F.

J. Y. Hardeberg, F. Schmitt, and H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41, 2532–2548 (2002).
[Crossref]

Seiler, C.

J. Brauers, C. Seiler, and T. Aach, “Direct PSF estimation using a random noise target,” Proc. SPIE 7537, 75370B (2010).
[Crossref]

Sejnowski, T. J.

E. Doi, T. Inue, T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Spatiochromatic receptive field properties derived from information-theoretic analyses of cone mosaic responses to natural scenes,” Neural Comput. 15, 397–417 (2003).
[Crossref]

T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Color opponency is an efficient representation of spectral properties in natural scenes,” Vis. Res. 42, 2095–2103 (2002).
[Crossref]

Selbig, J.

R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, “The mutual information: detecting and evaluating dependencies between variables,” Bioinformatics 18, S231–S240 (2002).
[Crossref]

Shapley, R.

R. Shapley and M. J. Hawken, “Color in the cortex: single- and double-opponent cells,” Vision Res. 51, 701–717 (2011).
[Crossref]

Sharpe, L. T.

A. Stockman and L. T. Sharpe, “The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype,” Vision Res. 40, 1711–1737 (2000).
[Crossref]

A. Stockman, L. T. Sharpe, and C. Fach, “The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches,” Vis. Res. 39, 2901–2927 (1999).
[Crossref]

A. Stockman and L. T. Sharpe, “Cone spectral sensitivities and color matching,” in Color Vision: From Genes To Perception, K. R. Gegenfurtner and L. T. Sharpe, eds. (Cambridge University, 1999), pp. 53–87.

Shevell, S. K.

Silverman, R.

S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, “An optimal algorithm for approximate nearest neighbor searching in fixed dimensions,” J. ACM 45, 891–923 (1998).
[Crossref]

Silverstein, D. A.

X. Zhang, D. A. Silverstein, J. E. Farrell, and B. A. Wandell, “Color image quality metric S-CIELAB and its application on halftone texture visibility,” in IEEE COMPCON 97 (IEEE, 1997), pp. 44–48.

Sims, D. A.

D. A. Sims and J. A. Gamon, “Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages,” Remote Sens. Environ. 81, 337–354 (2002).
[Crossref]

Smet, K. A. G.

Smith, V. C.

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Smithson, H. E.

T. Morimoto and H. E. Smithson, “Discrimination of spectral reflectance under environmental illumination,” J. Opt. Soc. Am. A 35, B244–B255 (2018).
[Crossref]

H. E. Smithson, “Sensory, computational and cognitive components of human colour constancy,” Philos. Trans. R. Soc. B. 360, 1329–1346 (2005).
[Crossref]

Stanislas, M.

D. G. Abdelsalam, M. Stanislas, and S. Coudert, “CCD or CMOS camera calibration using point spread function,” Proc. SPIE 9234, 92340Z (2014).
[Crossref]

Steuer, R.

R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, “The mutual information: detecting and evaluating dependencies between variables,” Bioinformatics 18, S231–S240 (2002).
[Crossref]

Stevenson, R. L.

R. Zhen and R. L. Stevenson, “Image demosaicing,” in Color Image and Video Enhancement, M. E. Celebi, M. Lecca, and B. Smolka, eds. (Springer, 2015), pp. 13–22.

Stiles, W. S.

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).

Stockman, A.

B. R. Conway, R. T. Eskew, P. R. Martin, and A. Stockman, “A tour of contemporary color vision research,” Vis. Res. 151, 2–6 (2018).
[Crossref]

A. Stockman and L. T. Sharpe, “The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype,” Vision Res. 40, 1711–1737 (2000).
[Crossref]

A. Stockman, L. T. Sharpe, and C. Fach, “The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches,” Vis. Res. 39, 2901–2927 (1999).
[Crossref]

A. Stockman and L. T. Sharpe, “Cone spectral sensitivities and color matching,” in Color Vision: From Genes To Perception, K. R. Gegenfurtner and L. T. Sharpe, eds. (Cambridge University, 1999), pp. 53–87.

D. H. Brainard and A. Stockman, “Colorimetry,” in Handbook of Optics. Volume III. Vision and Vision Optics, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 10.1–10.56.

Sun, P.-L.

P.-L. Sun and J. Morovic, “Inter-relating colour difference metrics,” in Tenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications (Society for Imaging Science and Technology, 2002), pp. 55–60.

Suomalainen, J.

Takahashi, T.

S. Watanabe, T. Takahashi, and K. Bennett, “Quantitative evaluation of the accuracy and variance of individual pixels in a scientific CMOS (sCMOS) camera for computational imaging,” Proc. SPIE 10071, 100710Z (2017).
[Crossref]

Tatol, M.

W. S. Mokrzycki and M. Tatol, “Colour difference ΔE–a survey,” Mach. Graph. Vis. 20, 383–411 (2011).

Terstiege, H.

H. Terstiege, “Chromatic adaptation: a state-of-the-art report,” J. Color Appearance 1, 19–23, 40 (1972).

Thomas, J. A.

T. M. Cover and J. A. Thomas, Elements of Information Theory, 2nd ed. (Wiley, 2006).

Thomas, J.-B.

H. A. Khan, S. Mihoubi, B. Mathon, J.-B. Thomas, and J. Y. Hardeberg, “HyTexiLa: high resolution visible and near infrared hyperspectral texture images,” Sensors 18, 2045 (2018).
[Crossref]

H. A. Khan, J.-B. Thomas, J. Y. Hardeberg, and O. Laligant, “Illuminant estimation in multispectral imaging,” J. Opt. Soc. Am. A 34, 1085–1098 (2017).
[Crossref]

X.-B. Wang, P. J. Green, J.-B. Thomas, J. Y. Hardeberg, and P. Gouton, “Evaluation of the colorimetric performance of single-sensor image acquisition systems employing colour and multispectral filter array,” in Computational Color Imaging, CCIW, A. Trémeau, R. Schettini, and S. Tominaga, eds. (Springer, 2015), pp. 181–191.

Thomson, K. P. B.

J. R. Miller, S. C. Jain, N. T. O’Neill, W. R. McNeil, and K. P. B. Thomson, “Interpretation of airborne spectral reflectance measurements over Georgian Bay,” Remote Sens. Environ. 6, 183–200 (1977).
[Crossref]

Thyagharajan, K. K.

K. S. Babu, V. Ramachandran, K. K. Thyagharajan, and G. Santhosh, “Hyperspectral image compression algorithms—a review,” in International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES), L. P. Suresh, S. S. Dash, and B. K. Panigrahi, eds. (Springer, 2015), Vol. 2, pp. 127–138.

Toadere, F.

F. Toadere, “Simulating the functionality of a digital camera pipeline,” Opt. Eng. 52, 102005 (2013).
[Crossref]

Tominaga, S.

Toscani, M.

Tremeau, A.

R. Deeb, D. Muselet, M. Hebert, and A. Tremeau, “Interreflections in computer vision: a survey and an introduction to spectral infinite-bounce model,” J. Math. Imaging Vis. 60, 661–680 (2018).
[Crossref]

Troscianko, T.

Urban, P.

S. Le Moan and P. Urban, “Image-difference prediction: from color to spectral,” IEEE Trans. Image Process. 23, 2058–2068 (2014).
[Crossref]

P. Urban, “Gamut volume,” in Encyclopedia of Color Science and Technology, M. R. Luo, ed. (Springer, 2016), pp. 676–678.

Uusitalo, H.

L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
[Crossref]

Vahimaa, P.

Vakalopoulou, M.

M. Vakalopoulou and K. Karantzalos, “Automatic descriptor-based co-registration of frame hyperspectral data,” Remote Sens. 6, 3409–3426 (2014).
[Crossref]

Valero, E. M.

van de Weijer, J.

A. Gijsenij, T. Gevers, and J. van de Weijer, “Computational color constancy: survey and experiments,” IEEE Trans. Image Process. 20, 2475–2489 (2011).
[Crossref]

Vanrell, M.

J. Roca-Vila, C. A. Parraga, and M. Vanrell, “Chromatic settings and the structural color constancy index,” J. Vis. 13 (4), 3 (2013).
[Crossref]

Vilarigues, M.

Viqueira, V.

Voisin, Y.

S. Le Moan, A. Mansouri, Y. Voisin, and J. Y. Hardeberg, “A constrained band selection method based on information measures for spectral image color visualization,” IEEE Trans. Geosci. Remote Sens. 49, 5104–5115 (2011).
[Crossref]

Vorhagen, F. W.

B. Hill, T. Roger, and F. W. Vorhagen, “Comparative analysis of the quantization of color spaces on the basis of the CIELAB color-difference formula,” ACM Trans. Graph. 16, 109–154 (1997).
[Crossref]

Vos, J. J.

J. J. Vos and P. L. Walraven, “On the derivation of the foveal receptor primaries,” Vis. Res. 11, 799–818 (1970).
[Crossref]

Wachman, E.

J. M. Lerner, N. Gat, and E. Wachman, “Approaches to spectral imaging hardware,” Curr. Protoc. Cytom. 53, 12–20 (2010).
[Crossref]

Wachtler, T.

E. Doi, T. Inue, T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Spatiochromatic receptive field properties derived from information-theoretic analyses of cone mosaic responses to natural scenes,” Neural Comput. 15, 397–417 (2003).
[Crossref]

T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Color opponency is an efficient representation of spectral properties in natural scenes,” Vis. Res. 42, 2095–2103 (2002).
[Crossref]

Walraven, P. L.

J. J. Vos and P. L. Walraven, “On the derivation of the foveal receptor primaries,” Vis. Res. 11, 799–818 (1970).
[Crossref]

Wandell, B. A.

X. Zhang, D. A. Silverstein, J. E. Farrell, and B. A. Wandell, “Color image quality metric S-CIELAB and its application on halftone texture visibility,” in IEEE COMPCON 97 (IEEE, 1997), pp. 44–48.

Wang, L. V.

L. Gao and L. V. Wang, “A review of snapshot multidimensional optical imaging: measuring photon tags in parallel,” Phys. Rep. 616, 1–37 (2016).
[Crossref]

Wang, X.-B.

X.-B. Wang, P. J. Green, J.-B. Thomas, J. Y. Hardeberg, and P. Gouton, “Evaluation of the colorimetric performance of single-sensor image acquisition systems employing colour and multispectral filter array,” in Computational Color Imaging, CCIW, A. Trémeau, R. Schettini, and S. Tominaga, eds. (Springer, 2015), pp. 181–191.

Wang, Y.

Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
[Crossref]

Wang, Z.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

Watanabe, S.

S. Watanabe, T. Takahashi, and K. Bennett, “Quantitative evaluation of the accuracy and variance of individual pixels in a scientific CMOS (sCMOS) camera for computational imaging,” Proc. SPIE 10071, 100710Z (2017).
[Crossref]

Webster, M. A.

Weise, J.

R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, “The mutual information: detecting and evaluating dependencies between variables,” Bioinformatics 18, S231–S240 (2002).
[Crossref]

Wenhe, L.

Westland, S.

V. Cheung and S. Westland, “Methods for optimal color selection,” J. Imaging Sci. Technol. 50, 481–488 (2006).
[Crossref]

S. Westland, C. Ripamonti, and V. Cheung, Computational Colour Science Using Matlab, 2nd ed. (Wiley, 2012).

S. Westland, University of Leeds (personal communication, 2018).

Y. Li, S. Westland, Q. Pan, and V. Cheung, “Methods to assess the relative number of discernible colors for displays,” in 22nd Color and Imaging Conference (Society for Imaging Science and Technology, 2014), pp. 151–154.

Whitehead, L. A.

Witzel, C.

C. Witzel and K. R. Gegenfurtner, “Color perception: objects, constancy, and categories,” Annu. Rev. Vis. Sci. 4, 475–499 (2018).
[Crossref]

Wolfe, W. L.

W. L. Wolfe, “Glossary and fundamental constants,” in Handbook of Optics, Volume 1, Geometrical and Physical Optics, Polarized Light, Components and Instruments, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. xxix–xxxiv.

Wu, A. Y.

S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, “An optimal algorithm for approximate nearest neighbor searching in fixed dimensions,” J. ACM 45, 891–923 (1998).
[Crossref]

Wyatt, C. L.

C. L. Wyatt, V. Privalsky, and R. Datla, Recommended practice: symbols, terms, units and uncertainty analysis for radiometric sensor calibration (National Institute of Standards and Technology, U.S. Department of Commerce Technology Administration, 1998).

Wyszecki, G.

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).

Xiang-li, B.

L.-L. Qian, Q.-B. Lü, M. Huang, Q.-S. Cai, and B. Xiang-li, “Effect of keystone on coded aperture spectral imaging,” Optik 127, 686–689 (2016).
[Crossref]

Xiao, R.

M. Paul, R. Xiao, J. B. Gao, and T. Bossomaier, “Reflectance prediction modelling for residual-based hyperspectral image coding,” PLoS ONE 11, e0161212 (2016).
[Crossref]

Xu, D.

Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
[Crossref]

Xu, Y.

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

Yau, K.-W.

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Yuan, X.

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

Yue, T.

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

Zele, A. J.

A. J. Zele and D. Cao, “Vision under mesopic and scotopic illumination,” Front. Psychol. 5, 1594, 1–15 (2015).
[Crossref]

Zhang, X.

X. Zhang, D. A. Silverstein, J. E. Farrell, and B. A. Wandell, “Color image quality metric S-CIELAB and its application on halftone texture visibility,” in IEEE COMPCON 97 (IEEE, 1997), pp. 44–48.

Zhaoping, L.

A. Lewis and L. Zhaoping, “Are cone sensitivities determined by natural color statistics?” J. Vis. 6 (3), 285–302 (2006).
[Crossref]

Zhen, R.

R. Zhen and R. L. Stevenson, “Image demosaicing,” in Color Image and Video Enhancement, M. E. Celebi, M. Lecca, and B. Smolka, eds. (Springer, 2015), pp. 13–22.

Ziemer, P.

P. Ziemer, “Design and implementation of a multispectral imaging system,” M.Sc. thesis (Department of Computer Science and Information Science, Universität Konstanz, 2013).

Zitová, B.

B. Zitová and J. Flusser, “Image registration methods: a survey,” Image Vis. Comput. 21, 977–1000 (2003).
[Crossref]

Zucco, M.

Zychaluk, K.

D. H. Foster and K. Żychaluk, “Is there a better non-parametric alternative to von Kries scaling?” in CGIV 2008, 4th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2008), pp. 41–44.

ACM Trans. Graph. (1)

B. Hill, T. Roger, and F. W. Vorhagen, “Comparative analysis of the quantization of color spaces on the basis of the CIELAB color-difference formula,” ACM Trans. Graph. 16, 109–154 (1997).
[Crossref]

Am. J. Bot. (1)

J. H. McClendon, “The micro-optics of leaves. I. Patterns of reflection from the epidermis,” Am. J. Bot. 71, 1391–1397 (1984).
[Crossref]

Annu. Rev. Vis. Sci. (1)

C. Witzel and K. R. Gegenfurtner, “Color perception: objects, constancy, and categories,” Annu. Rev. Vis. Sci. 4, 475–499 (2018).
[Crossref]

Appl. Opt. (4)

Appl. Phys. A (1)

H. Liang, “Advances in multispectral and hyperspectral imaging for archaeology and art conservation,” Appl. Phys. A 106, 309–323 (2012).
[Crossref]

Bioinformatics (1)

R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, “The mutual information: detecting and evaluating dependencies between variables,” Bioinformatics 18, S231–S240 (2002).
[Crossref]

Biomed. Signal Process. Control (1)

L. Laaksonen, E. Claridge, P. Fält, M. Hauta-Kasari, H. Uusitalo, and L. Lensu, “Comparison of image registration methods for composing spectral retinal images,” Biomed. Signal Process. Control 36, 234–245 (2017).
[Crossref]

Chemom. Intell. Lab. Syst. (1)

P. Geladi, J. Burger, and T. Lestlander, “Hyperspectral imaging: calibration problems and solutions,” Chemom. Intell. Lab. Syst. 72, 209–217 (2004).
[Crossref]

Color Res. Appl. (11)

K. Barnard and B. Funt, “Camera characterization for color research,” Color Res. Appl. 27, 152–163 (2002).
[Crossref]

H. S. Fairman, “An improved method for correcting radiance data for bandpass error,” Color Res. Appl. 35, 328–333 (2010).
[Crossref]

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera and colored filters,” Color Res. Appl. 32, 352–360 (2007).
[Crossref]

C. Li, M. R. Luo, B. Rigg, and R. W. G. Hunt, “CMC 2000 chromatic adaptation transform: CMCCAT2000,” Color Res. Appl. 27, 49–58 (2002).
[Crossref]

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31, 320–330 (2006).
[Crossref]

C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, and M. Pointer, “Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS,” Color Res. Appl. 42, 703–718 (2017).
[Crossref]

M. R. Pointer and G. G. Attridge, “The number of discernible colours,” Color Res. Appl. 23, 52–54 (1998).
[Crossref]

G. M. Johnson and M. D. Fairchild, “A top down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
[Crossref]

J. L. Nieves and J. Romero, “Heuristic analysis influence of saliency in the color diversity of natural images,” Color Res. Appl. 43, 713–725 (2018).
[Crossref]

M. R. Luo and R. W. G. Hunt, “A chromatic adaptation transform and a colour inconstancy index,” Color Res. Appl. 23, 154–158 (1998).
[Crossref]

CRC Crit. Rev. Anal. Chem. (1)

H. K. Lichtenthaler and U. Rinderle, “The role of chlorophyll fluorescence in the detection of stress conditions in plants,” CRC Crit. Rev. Anal. Chem. 19, S29–S85 (1988).
[Crossref]

Curr. Protoc. Cytom. (1)

J. M. Lerner, N. Gat, and E. Wachman, “Approaches to spectral imaging hardware,” Curr. Protoc. Cytom. 53, 12–20 (2010).
[Crossref]

Entropy (1)

M. Grendar, “Entropy and effective support size,” Entropy 8, 169–174 (2006).
[Crossref]

Eye (1)

T. D. Lamb, “Why rods and cones?” Eye 30, 179–185 (2016).
[Crossref]

Front. Psychol. (1)

A. J. Zele and D. Cao, “Vision under mesopic and scotopic illumination,” Front. Psychol. 5, 1594, 1–15 (2015).
[Crossref]

IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. (2)

R. Heylen, M. Parente, and P. Gader, “A review of nonlinear hyperspectral unmixing methods,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 7, 1844–1868 (2014).
[Crossref]

J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches,” IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 5, 354–379 (2012).
[Crossref]

IEEE Signal Process. Mag. (1)

X. Cao, T. Yue, X. Lin, S. Lin, X. Yuan, Q.-H. Dai, L. Carin, and D. J. Brady, “Computational snapshot multispectral cameras: toward dynamic capture of the spectral world,” IEEE Signal Process. Mag. 33(5), 95–108 (2016).
[Crossref]

IEEE Trans. Geosci. Remote Sens. (1)

S. Le Moan, A. Mansouri, Y. Voisin, and J. Y. Hardeberg, “A constrained band selection method based on information measures for spectral image color visualization,” IEEE Trans. Geosci. Remote Sens. 49, 5104–5115 (2011).
[Crossref]

IEEE Trans. Image Process. (4)

A. Gijsenij, R. Lu, and T. Gevers, “Color constancy for multiple light sources,” IEEE Trans. Image Process. 21, 697–707 (2012).
[Crossref]

L. Gu, C. P. Huynh, and A. Robles-Kelly, “Segmentation and estimation of spatially varying illumination,” IEEE Trans. Image Process. 23, 3478–3489 (2014).
[Crossref]

S. Le Moan and P. Urban, “Image-difference prediction: from color to spectral,” IEEE Trans. Image Process. 23, 2058–2068 (2014).
[Crossref]

A. Gijsenij, T. Gevers, and J. van de Weijer, “Computational color constancy: survey and experiments,” IEEE Trans. Image Process. 20, 2475–2489 (2011).
[Crossref]

IEEE Trans. Inf. Theory (1)

A. Lapidoth, “Nearest neighbor decoding for additive non-Gaussian noise channels,” IEEE Trans. Inf. Theory 42, 1520–1529 (1996).
[Crossref]

IEEE Trans. Pattern Anal. Mach. Intell. (2)

I. Marín-Franch and D. H. Foster, “Estimating Information from image colors: an application to digital cameras and natural scenes,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 78–91 (2013).
[Crossref]

B. V. Funt and M. S. Drew, “Color space analysis of mutual illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1319–1326 (1993).
[Crossref]

Image Vis. Comput. (1)

B. Zitová and J. Flusser, “Image registration methods: a survey,” Image Vis. Comput. 21, 977–1000 (2003).
[Crossref]

Imaging Sci. J. (1)

M. R. Pointer, G. G. Attridge, and R. E. Jacobson, “Practical camera characterization for colour measurement,” Imaging Sci. J. 49, 63–80 (2001).
[Crossref]

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. (1)

T. H. Kurz and S. J. Buckley, “A review of hyperspectral imaging in close range applications,” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XLI-B5, 865–870 (2016).
[Crossref]

Int. J. Comput. Vis. (1)

B. V. Funt, M. S. Drew, and J. Ho, “Color constancy from mutual reflection,” Int. J. Comput. Vis. 6, 5–24 (1991).
[Crossref]

Int. J. Robot. Autom. (1)

A. Mansouri, F. S. Marzani, and P. Gouton, “Development of a protocol for CCD calibration: application to a multispectral imaging system,” Int. J. Robot. Autom. 20, 94–100 (2005).

ISPRS J. Photogramm. Remote Sens. (1)

T. Luhmann, C. Fraser, and H.-G. Maas, “Sensor modelling and camera calibration for close-range photogrammetry,” ISPRS J. Photogramm. Remote Sens. 115, 37–46 (2016).
[Crossref]

J. ACM (1)

S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, “An optimal algorithm for approximate nearest neighbor searching in fixed dimensions,” J. ACM 45, 891–923 (1998).
[Crossref]

J. Biomed. Opt. (1)

Q. Li, X. He, Y. Wang, H. Liu, D. Xu, and F. Guo, “Review of spectral imaging technology in biomedical engineering: achievements and challenges,” J. Biomed. Opt. 18, 100901 (2013).
[Crossref]

J. Chemom. (1)

J. Burger and P. Geladi, “Hyperspectral NIR image regression, part I: calibration and correction,” J. Chemom. 19, 355–363 (2005).
[Crossref]

J. Color Appearance (1)

H. Terstiege, “Chromatic adaptation: a state-of-the-art report,” J. Color Appearance 1, 19–23, 40 (1972).

J. Imaging Sci. Technol. (4)

V. Cheung and S. Westland, “Methods for optimal color selection,” J. Imaging Sci. Technol. 50, 481–488 (2006).
[Crossref]

V. C. Cardei and B. Funt, “Color correcting uncalibrated digital images,” J. Imaging Sci. Technol. 44, 288–378 (2000).

M. A. López-Álvarez, J. Hernández-Andrés, J. Romero, J. Campos, and A. Pons, “Calibrating the elements of a multispectral imaging system,” J. Imaging Sci. Technol. 53, 031102 (2009).
[Crossref]

A. M. Bakke, I. Farup, and J. Y. Hardeberg, “Evaluation of algorithms for the determination of color gamut boundaries,” J. Imaging Sci. Technol. 54, 050502 (2010).
[Crossref]

J. Math. Imaging Vis. (1)

R. Deeb, D. Muselet, M. Hebert, and A. Tremeau, “Interreflections in computer vision: a survey and an introduction to spectral infinite-bounce model,” J. Math. Imaging Vis. 60, 661–680 (2018).
[Crossref]

J. Nonparametr. Stat. (1)

M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. Novi Inverardi, “A new class of random vector entropy estimators and its applications in testing statistical hypotheses,” J. Nonparametr. Stat. 17, 277–297 (2005).
[Crossref]

J. Opt. Soc. Am. (2)

J. Opt. Soc. Am. A (31)

P. A. Barrionuevo and D. C. Cao, “Contributions of rhodopsin, cone opsins, and melanopsin to postreceptoral pathways inferred from natural image statistics,” J. Opt. Soc. Am. A 31, A131–A139(2014).
[Crossref]

C. A. Párraga, G. Brelstaff, T. Troscianko, and I. R. Moorehead, “Color and luminance information in natural scenes,” J. Opt. Soc. Am. A 15, 563–569 (1998).
[Crossref]

I. Fine, D. I. A. MacLeod, and G. M. Boynton, “Surface segmentation based on the luminance and color statistics of natural scenes,” J. Opt. Soc. Am. A 20, 1283–1291 (2003).
[Crossref]

F. Martínez-Verdú, E. Perales, E. Chorro, D. de Fez, V. Viqueira, and E. Gilabert, “Computation and visualization of the MacAdam limits for any lightness, hue angle, and light source,” J. Opt. Soc. Am. A 24, 1501–1515 (2007).
[Crossref]

M. Flinkman, H. Laamanen, P. Vahimaa, and M. Hauta-Kasari, “Number of colors generated by smooth nonfluorescent reflectance spectra,” J. Opt. Soc. Am. A 29, 2566–2575 (2012).
[Crossref]

D. H. Foster, I. Marín-Franch, K. Amano, and S. M. C. Nascimento, “Approaching ideal observer efficiency in using color to retrieve information from natural scenes,” J. Opt. Soc. Am. A 26, B14–B24 (2009).
[Crossref]

S. K. Shevell and P. R. Martin, “Color opponency: tutorial,” J. Opt. Soc. Am. A 34, 1099–1108 (2017).
[Crossref]

D. L. Ruderman, T. W. Cronin, and C.-C. Chiao, “Statistics of cone responses to natural images: implications for visual coding,” J. Opt. Soc. Am. A 15, 2036–2045 (1998).
[Crossref]

S. Tominaga, K. Kato, K. Hirai, and T. Horiuchi, “Spectral image analysis of mutual illumination between florescent objects,” J. Opt. Soc. Am. A 33, 1476–1487 (2016).
[Crossref]

H. A. Khan, J.-B. Thomas, J. Y. Hardeberg, and O. Laligant, “Illuminant estimation in multispectral imaging,” J. Opt. Soc. Am. A 34, 1085–1098 (2017).
[Crossref]

G. D. Finlayson, M. S. Drew, and B. V. Funt, “Spectral sharpening: sensor transformations for improved color constancy,” J. Opt. Soc. Am. A 11, 1553–1563 (1994).
[Crossref]

D. K. Prasad and L. Wenhe, “Metrics and statistics of frequency of occurrence of metamerism in consumer cameras for natural scenes,” J. Opt. Soc. Am. A 32, 1390–1402 (2015).
[Crossref]

M. Melgosa, R. Huertas, and R. S. Berns, “Performance of recent advanced color-difference formulas using the standardized residual sum of squares index,” J. Opt. Soc. Am. A 25, 1828–1834 (2008).
[Crossref]

K. A. G. Smet, M. A. Webster, and L. A. Whitehead, “A simple principled approach for modeling and understanding uniform color metrics,” J. Opt. Soc. Am. A 33, A319–A331 (2016).
[Crossref]

J. M. M. Linhares, P. D. A. Pinto, and S. M. C. Nascimento, “Color rendering of art paintings under CIE illuminants for normal and color deficient observers,” J. Opt. Soc. Am. A 26, 1668–1677 (2009).
[Crossref]

C. Montagner, J. M. M. Linhares, M. Vilarigues, and S. M. C. Nascimento, “Statistics of colors in paintings and natural scenes,” J. Opt. Soc. Am. A 33, A170–A177 (2016).
[Crossref]

M. Brady and G. E. Legge, “Camera calibration for natural image studies and vision research,” J. Opt. Soc. Am. A 26, 30–42 (2009).
[Crossref]

R. Ennis, F. Schiller, M. Toscani, and K. R. Gegenfurtner, “Hyperspectral database of fruits and vegetables,” J. Opt. Soc. Am. A 35, B256–B266 (2018).
[Crossref]

R. Dusselaar and M. Paul, “Hyperspectral image compression approaches: opportunities, challenges, and future directions: discussion,” J. Opt. Soc. Am. A 34, 2170–2180 (2017).
[Crossref]

F. Gori and P. S. Carney, “Introducing JOSA A tutorials: editorial,” J. Opt. Soc. Am. A 32, ED3 (2015).
[Crossref]

J. Hernández-Andrés, J. Romero, and J. L. Nieves, “Color and spectral analysis of daylight in southern Europe,” J. Opt. Soc. Am. A 18, 1325–1335 (2001).
[Crossref]

D. H. Foster, K. Amano, S. M. C. Nascimento, and M. J. Foster, “Frequency of metamerism in natural scenes,” J. Opt. Soc. Am. A 23, 2359–2372 (2006).
[Crossref]

A. Akbarinia and K. R. Gegenfurtner, “Color metamerism and the structure of illuminant space,” J. Opt. Soc. Am. A 35, B231–B238 (2018).
[Crossref]

D. H. Foster, “The Verriest lecture: color vision in an uncertain world,” J. Opt. Soc. Am. A 35, B192–B201 (2018).
[Crossref]

J. M. M. Linhares, P. D. Pinto, and S. M. C. Nascimento, “The number of discernible colors in natural scenes,” J. Opt. Soc. Am. A 25, 2918–2924 (2008).
[Crossref]

L. E. Arend, A. Reeves, J. Schirillo, and R. Goldstein, “Simultaneous color constancy: papers with diverse Munsell values,” J. Opt. Soc. Am. A 8, 661–672 (1991).
[Crossref]

D. H. Brainard, “Color constancy in the nearly natural image. 2. Achromatic loci,” J. Opt. Soc. Am. A 15, 307–325 (1998).
[Crossref]

Y. Ling and A. Hurlbert, “Role of color memory in successive color constancy,” J. Opt. Soc. Am. A 25, 1215–1226 (2008).
[Crossref]

T. Morimoto and H. E. Smithson, “Discrimination of spectral reflectance under environmental illumination,” J. Opt. Soc. Am. A 35, B244–B255 (2018).
[Crossref]

G. Feng and D. H. Foster, “Predicting frequency of metamerism in natural scenes by entropy of colors,” J. Opt. Soc. Am. A 29, A200–A208 (2012).
[Crossref]

N. Fider and N. L. Komarova, “Quantitative study of color category boundaries,” J. Opt. Soc. Am. A 35, B165–B183 (2018).
[Crossref]

J. Physiol. (1)

A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. 357, 241–265 (1984).
[Crossref]

J. Vis. (4)

D. H. Brainard and L. T. Maloney, “Surface color perception and equivalent illumination models,” J. Vis. 11(5), 1 (2011).
[Crossref]

A. Lewis and L. Zhaoping, “Are cone sensitivities determined by natural color statistics?” J. Vis. 6 (3), 285–302 (2006).
[Crossref]

J. Roca-Vila, C. A. Parraga, and M. Vanrell, “Chromatic settings and the structural color constancy index,” J. Vis. 13 (4), 3 (2013).
[Crossref]

I. Marín-Franch and D. H. Foster, “Number of perceptually distinct surface colors in natural scenes,” J. Vis. 10(9), 9 (2010).
[Crossref]

Mach. Graph. Vis. (1)

W. S. Mokrzycki and M. Tatol, “Colour difference ΔE–a survey,” Mach. Graph. Vis. 20, 383–411 (2011).

Nat. Photonics (1)

D. Bannon, “Hyperspectral imaging: cubes and slices,” Nat. Photonics 3, 627–629 (2009).
[Crossref]

Nature (1)

D. M. Dacey, H.-W. Liao, B. B. Peterson, F. R. Robinson, V. C. Smith, J. Pokorny, K.-W. Yau, and P. D. Gamlin, “Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN,” Nature 433, 749–754 (2005).
[Crossref]

Neural Comput. (1)

E. Doi, T. Inue, T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Spatiochromatic receptive field properties derived from information-theoretic analyses of cone mosaic responses to natural scenes,” Neural Comput. 15, 397–417 (2003).
[Crossref]

Ophthalmic Physiolog. Opt. (1)

J. M. M. Linhares, P. E. R. Felgueiras, P. D. Pinto, and S. M. C. Nascimento, “Colour rendering of indoor lighting with CIE illuminants and white LEDs for normal and colour deficient observers,” Ophthalmic Physiolog. Opt. 30, 618–625 (2010).
[Crossref]

Opt. Eng. (5)

C. V. Correa, C. A. Hinojosa, G. R. Arce, and H. Arguello, “Multiple snapshot colored compressive spectral imager,” Opt. Eng. 56, 041309 (2016).
[Crossref]

T. F. Blake, S. C. Cain, and M. E. Goda, “Enhancing the resolution of spectral images from the advanced electro-optical system spectral imaging sensor,” Opt. Eng. 46, 057001 (2007).
[Crossref]

F. Toadere, “Simulating the functionality of a digital camera pipeline,” Opt. Eng. 52, 102005 (2013).
[Crossref]

N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013).
[Crossref]

J. Y. Hardeberg, F. Schmitt, and H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41, 2532–2548 (2002).
[Crossref]

Opt. Express (2)

Opt. Photon. News (1)

V. C. Coffey, “Hyperspectral imaging for safety and security,” Opt. Photon. News 26, 28–33 (2015).

Optik (1)

L.-L. Qian, Q.-B. Lü, M. Huang, Q.-S. Cai, and B. Xiang-li, “Effect of keystone on coded aperture spectral imaging,” Optik 127, 686–689 (2016).
[Crossref]

Pattern Recogn. (1)

J. Salvi, X. Armangué, and J. Batlle, “A comparative review of camera calibrating methods with accuracy evaluation,” Pattern Recogn. 35, 1617–1635 (2002).
[Crossref]

Philos. Trans. R. Soc. B. (1)

H. E. Smithson, “Sensory, computational and cognitive components of human colour constancy,” Philos. Trans. R. Soc. B. 360, 1329–1346 (2005).
[Crossref]

Photochem. Photobiol. (2)

J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. I. Introduction and the correction of leaf spectra for surface reflection,” Photochem. Photobiol. 51, 203–210 (1990).
[Crossref]

J. H. McClendon and L. Fukshansky, “On the interpretation of absorption spectra of leaves. II. The non-absorbed ray of the sieve effect and the mean optical pathlength in the remainder of the leaf,” Photochem. Photobiol. 51, 211–216 (1990).
[Crossref]

Phys. Rep. (1)

L. Gao and L. V. Wang, “A review of snapshot multidimensional optical imaging: measuring photon tags in parallel,” Phys. Rep. 616, 1–37 (2016).
[Crossref]

Plant Physiol. (1)

J. B. Clark and G. R. Lister, “Photosynthetic action spectra of trees. II. The relationship of cuticle structure to the visible and ultraviolet spectral properties of needles from four coniferous species,” Plant Physiol. 55, 407–413 (1975).
[Crossref]

PLoS ONE (1)

M. Paul, R. Xiao, J. B. Gao, and T. Bossomaier, “Reflectance prediction modelling for residual-based hyperspectral image coding,” PLoS ONE 11, e0161212 (2016).
[Crossref]

Probl. Inf. Transm. (1)

L. F. Kozachenko and N. N. Leonenko, “Sample estimate of the entropy of a random vector,” Probl. Inf. Transm. 23, 95–101(1987).

Proc. R. Soc. London B (1)

G. Buchsbaum and A. Gottschalk, “Trichromacy, opponent colours coding and optimum colour information transmission in the retina,” Proc. R. Soc. London B 220, 89–113 (1983).
[Crossref]

Proc. SPIE (5)

S. Watanabe, T. Takahashi, and K. Bennett, “Quantitative evaluation of the accuracy and variance of individual pixels in a scientific CMOS (sCMOS) camera for computational imaging,” Proc. SPIE 10071, 100710Z (2017).
[Crossref]

N. Gat, “Imaging spectroscopy using tunable filters: a review,” Proc. SPIE 4056, 50–64 (2000).
[Crossref]

D. G. Abdelsalam, M. Stanislas, and S. Coudert, “CCD or CMOS camera calibration using point spread function,” Proc. SPIE 9234, 92340Z (2014).
[Crossref]

E. Buhr, S. Günther-Kohfahl, and U. Neitzel, “Simple method for modulation transfer function determination of digital imaging detectors from edge images,” Proc. SPIE 5030, 877–884 (2003).
[Crossref]

J. Brauers, C. Seiler, and T. Aach, “Direct PSF estimation using a random noise target,” Proc. SPIE 7537, 75370B (2010).
[Crossref]

Remote Sens. (1)

M. Vakalopoulou and K. Karantzalos, “Automatic descriptor-based co-registration of frame hyperspectral data,” Remote Sens. 6, 3409–3426 (2014).
[Crossref]

Remote Sens. Environ. (3)

J. R. Miller, S. C. Jain, N. T. O’Neill, W. R. McNeil, and K. P. B. Thomson, “Interpretation of airborne spectral reflectance measurements over Georgian Bay,” Remote Sens. Environ. 6, 183–200 (1977).
[Crossref]

G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing—definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006).
[Crossref]

D. A. Sims and J. A. Gamon, “Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages,” Remote Sens. Environ. 81, 337–354 (2002).
[Crossref]

Sci. Total Environ. (1)

P. K. E. Campbell, E. M. Middleton, L. A. Corp, and M. S. Kim, “Contribution of chlorophyll fluorescence to the apparent vegetation reflectance,” Sci. Total Environ. 404, 433–439 (2008).
[Crossref]

Sensors (1)

H. A. Khan, S. Mihoubi, B. Mathon, J.-B. Thomas, and J. Y. Hardeberg, “HyTexiLa: high resolution visible and near infrared hyperspectral texture images,” Sensors 18, 2045 (2018).
[Crossref]

Vis. Res. (9)

S. M. C. Nascimento, J. M. M. Linhares, C. Montagner, C. A. R. João, K. Amano, C. Alfaro, and A. Bailão, “The colors of paintings and viewers’ preferences,” Vis. Res. 130, 76–84 (2017).
[Crossref]

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Time-lapse ratios of cone excitations in natural scenes,” Vis. Res. 120, 45–60(2016).
[Crossref]

S. M. C. Nascimento, K. Amano, and D. H. Foster, “Spatial distributions of local illumination color in natural scenes,” Vis. Res. 120, 39–44 (2016).
[Crossref]

T.-W. Lee, T. Wachtler, and T. J. Sejnowski, “Color opponency is an efficient representation of spectral properties in natural scenes,” Vis. Res. 42, 2095–2103 (2002).
[Crossref]

J. J. Vos and P. L. Walraven, “On the derivation of the foveal receptor primaries,” Vis. Res. 11, 799–818 (1970).
[Crossref]

A. Stockman, L. T. Sharpe, and C. Fach, “The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches,” Vis. Res. 39, 2901–2927 (1999).
[Crossref]

D. H. Foster, “Color constancy,” Vis. Res. 51, 674–700 (2011).
[Crossref]

E. Provenzi, J. Delon, Y. Gousseau, and B. Mazin, “On the second order spatiochromatic structure of natural images,” Vis. Res. 120, 22–38 (2016).
[Crossref]

B. R. Conway, R. T. Eskew, P. R. Martin, and A. Stockman, “A tour of contemporary color vision research,” Vis. Res. 151, 2–6 (2018).
[Crossref]

Vision Res. (2)

A. Stockman and L. T. Sharpe, “The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype,” Vision Res. 40, 1711–1737 (2000).
[Crossref]

R. Shapley and M. J. Hawken, “Color in the cortex: single- and double-opponent cells,” Vision Res. 51, 701–717 (2011).
[Crossref]

Other (51)

D. M. Mount and S. Arya, “ANN: a library for approximate nearest neighbor searching, version 1.1.2,” (University of Maryland, 2010).

W. K. Pratt, Digital Image Processing, 4th ed. (Wiley, 2007).

J. Morovič, Color Gamut Mapping (Wiley, 2008).

A. Stockman and L. T. Sharpe, “Cone spectral sensitivities and color matching,” in Color Vision: From Genes To Perception, K. R. Gegenfurtner and L. T. Sharpe, eds. (Cambridge University, 1999), pp. 53–87.

X. Zhang, D. A. Silverstein, J. E. Farrell, and B. A. Wandell, “Color image quality metric S-CIELAB and its application on halftone texture visibility,” in IEEE COMPCON 97 (IEEE, 1997), pp. 44–48.

P.-L. Sun and J. Morovic, “Inter-relating colour difference metrics,” in Tenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications (Society for Imaging Science and Technology, 2002), pp. 55–60.

S. Westland, University of Leeds (personal communication, 2018).

Y. Li, S. Westland, Q. Pan, and V. Cheung, “Methods to assess the relative number of discernible colors for displays,” in 22nd Color and Imaging Conference (Society for Imaging Science and Technology, 2014), pp. 151–154.

J. Morovic, V. Cheung, and P. Morovic, “Why we don’t know how many colors there are,” in CGIV 2012, 6th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2012), pp. 49–53.

R. Bala, G. Finlayson, and C. Lee, “Computational color imaging,” in Handbook of Convex Optimization Methods in Imaging Science, V. Monga, ed. (Springer, 2017), pp. 43–70.

IEC, “Colour management in multimedia systems–Part 2: colour management, Part 2.1: default RGB colour space–sRGB,” International Electrotechnical Commission, , 1998.

W. Cowan, “Displays for vision research,” in Handbook of Optics. Volume III. Vision and Vision Optics, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 22.1–22.41.

E. Reinhard, E. A. Khan, A. O. Akyüz, and G. M. Johnson, Color Imaging: Fundamentals and Applications (A. K. Peters, 2008).

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).

D. Lee, Nature’s Palette: The Science of Plant Color (University of Chicago, 2007).

R. C. Love, Surface Reflection Model Estimation from Naturally Illuminated Image Sequences (School of Computer Studies, University of Leeds, 1997).

N. Ekpenyong, Hyperspectral Imaging: Calibration and Applications with Natural Scenes (School of Electrical and Electronic Engineering University of Manchester, 2013).

P. Ziemer, “Design and implementation of a multispectral imaging system,” M.Sc. thesis (Department of Computer Science and Information Science, Universität Konstanz, 2013).

J. R. Janesick, Photon Transfer DN → λ (SPIE, 2007).

S. B. Howell, Handbook of CCD Astronomy, 2nd ed., Cambridge Observing Handbooks for Research Astronomers (Cambridge University, 2006).

H. F. Grahn and P. Geladi, eds., Techniques and Applications of Hyperspectral Image Analysis (Wiley, 2007).

K. S. Babu, V. Ramachandran, K. K. Thyagharajan, and G. Santhosh, “Hyperspectral image compression algorithms—a review,” in International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES), L. P. Suresh, S. S. Dash, and B. K. Panigrahi, eds. (Springer, 2015), Vol. 2, pp. 127–138.

S. K. Shevell, ed., The Science of Color, 2nd ed. (Elsevier, 2003).

D. H. Brainard and A. Stockman, “Colorimetry,” in Handbook of Optics. Volume III. Vision and Vision Optics, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 10.1–10.56.

D. H. Foster, “Chromatic function of the cones,” in Encyclopedia of the Eye, D. A. Dartt, ed. (Academic, 2010), pp. 266–274.

S. Westland, C. Ripamonti, and V. Cheung, Computational Colour Science Using Matlab, 2nd ed. (Wiley, 2012).

M. D. Fairchild, Color Appearance Models, 2nd ed. (Wiley, 2013).

L. Arend, “Environmental challenges to color constancy,” in Human Vision and Electronic Imaging VI, B. E. Rogowitz and T. N. Pappas, eds. (SPIE, 2001), pp. 392–399.

Munsell Color Company, Munsell Book of Color–Matte Finish Collection (Munsell Color Corporation, 1976).

UNESCO, International Classification and Mapping of Vegetation (UNESCO, 1973).

Federal Geographic Data Committee, “Vegetation classification standard,” U.S. Geological Survey, , 1997.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, Geometrical considerations and nomenclature for reflectance (Institute for Basic Standards/National Bureau of Standards, 1997).

C. L. Wyatt, V. Privalsky, and R. Datla, Recommended practice: symbols, terms, units and uncertainty analysis for radiometric sensor calibration (National Institute of Standards and Technology, U.S. Department of Commerce Technology Administration, 1998).

W. L. Wolfe, “Glossary and fundamental constants,” in Handbook of Optics, Volume 1, Geometrical and Physical Optics, Polarized Light, Components and Instruments, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. xxix–xxxiv.

CIE, “A colour appearance model for colour management systems: CIECAM02,” CIE Central Bureau, , 2004.

CIE, “Colorimetry, 4th Edition,” CIE Central Bureau, , 2018.

R. Kingslake and R. B. Johnson, Lens Design Fundamentals, 2nd ed. (Academic/SPIE, 2010).

P. A. Jansson and R. P. Breault, “Correcting color-measurement error caused by stray light in image scanners,” in Sixth Color and Imaging Conference: Color Science, Systems, and Applications (Society for Imaging Science and Technology, 1998), pp. 69–73.

S. Helling, “Improvement of multispectral image capture by compensating for stray light,” in CGIV 2006, 3rd European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2006), pp. 458–462.

J. M. Palmer, “Radiometry and photometry: units and conversions,” in Handbook of Optics, Volume II, Design, Fabrication, and Testing; Sources and Detectors; Radiometry and Photometry, M. Bass, ed., 3rd ed. (McGraw Hill, 2010), pp. 36.1–36.19.

P. Jerram, D. Burt, D. Morris, T. Eaton, and M. Fryer, “Design of image sensors for hyperspectral applications,” in Sensors, Systems, and Next-Generation Satellites XIII, R. Meynart, S. P. Neeck, and H. Shimoda, eds. (SPIE, 2009), pp. 74741E1.

F. H. Imai and R. S. Berns, “Spectral estimation using trichromatic digital cameras,” in International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42–49.

R. Zhen and R. L. Stevenson, “Image demosaicing,” in Color Image and Video Enhancement, M. E. Celebi, M. Lecca, and B. Smolka, eds. (Springer, 2015), pp. 13–22.

X.-B. Wang, P. J. Green, J.-B. Thomas, J. Y. Hardeberg, and P. Gouton, “Evaluation of the colorimetric performance of single-sensor image acquisition systems employing colour and multispectral filter array,” in Computational Color Imaging, CCIW, A. Trémeau, R. Schettini, and S. Tominaga, eds. (Springer, 2015), pp. 181–191.

F. H. Imai, M. R. Rosen, and R. S. Berns, “Comparison of spectrally narrow-band capture versus wide-band with a priori sample analysis for spectral reflectance estimation,” in Eighth Color Imaging Conference: Color Science and Engineering: Systems, Technologies and Applications (Society for Imaging Science and Technology, 2000), pp. 234–241.

D. H. Foster and K. Żychaluk, “Is there a better non-parametric alternative to von Kries scaling?” in CGIV 2008, 4th European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, 2008), pp. 41–44.

G. J. Klir, Uncertainty and Information: Foundations of Generalized Information Theory (Wiley, 2006).

C. Arndt, Information Measures: Information and its Description in Science and Engineering (Springer, 2001).

D. J. C. MacKay, Information Theory, Inference, and Learning Algorithms (Cambridge University, 2003).

T. M. Cover and J. A. Thomas, Elements of Information Theory, 2nd ed. (Wiley, 2006).

P. Urban, “Gamut volume,” in Encyclopedia of Color Science and Technology, M. R. Luo, ed. (Springer, 2016), pp. 676–678.

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (7)

Fig. 1.
Fig. 1. Examples of reflected radiance spectra from a flower scene. Data are from a hyperspectral radiance image of size 1344×1024pixels, corresponding to approximately 14×11deg visual angle at the camera, with spectra sampled at 400nm,410nm,,720nm. The plots show radiance spectra at individual pixels (radiance scales adjusted for range). The small light-gray sphere near the top of the scene is covered in Munsell N7 matte paint [4], and the reflected spectrum (top right plot) follows the typically uneven spectrum of light from the sun and sky [5]. The long, thin, light-gray rectangular plate at the bottom of the scene is a reference reflectance surface. The hyperspectral image of the scene was acquired on October 10, 2003, from a garden in Sameiro in the Minho region of Portugal.
Fig. 2.
Fig. 2. Grayscale wavelength slices from the hyperspectral radiance image of the flower scene in Fig. 1, with wavelength indicated in nm at the top left of each slice. The intensity range in each slice image has been stretched for illustration. As evident from the spectral radiance plots in Fig. 1, the surfaces in the scene reflect little energy at very short wavelengths.
Fig. 3.
Fig. 3. Effect of registration across wavelength. The color images of the stone cottage are rendered from a hyperspectral radiance image without registration, top left, and with registration, top right. Color fringing due to lateral chromatic aberration and its removal by registration can be seen more easily in the enlarged copies of the square areas marked in white, bottom left and bottom right, respectively. The long, thin, light-gray rectangular plate at the bottom of the full scene is a reference reflectance surface. The hyperspectral image of the cottage was acquired on June 4, 2003, under an overcast sky in Ruivães in the Minho region of Portugal.
Fig. 4.
Fig. 4. Real and simulated changes in illumination on a rock face. The color images in (a) and (b) are rendered from two time-lapse hyperspectral radiance images acquired at 18:15 and 18:40 [93]. The image in (c) is rendered from a simulated version of the spectral radiance image in (b) in which a global illuminant is applied to an effective spectral reflectance image derived from the spectral radiance image in (a). The real image in (b) and the simulated one in (c) are closely similar. The images in (d), (e), and (f) are analogous, except that (d) and (e) are from earlier in the day, at 13:21 and 15:15, and show marked changes in the distribution of shadows. The real image in (e) and the simulated one in (f) are clearly different. The small light-gray rectangular plate at the bottom of the scene, arrowed in (a), is a reference reflectance surface. The hyperspectral images of the rock face were acquired on October 6, 2003, in Sete Fontes in the Minho region of Portugal [93].
Fig. 5.
Fig. 5. Color rendering of a hyperspectral radiance image of a yellow flower. An sRGB image is shown left and a clipped and scaled version shown right, with the clip level taken from the arrowed area on the light-gray sphere in the left image. The percentage of clipped pixels is about 1%. The hyperspectral image of the flower was acquired on July 31, 2002, in Gualtar in the Minho region of Portugal.
Fig. 6.
Fig. 6. Physical limits on color constancy under a global illuminant change. The images top left and top right are color renderings of a hyperspectral reflectance image of a terrace with flowers under a global daylight illuminant with respective correlated color temperatures 4000 K and 6500 K. Enlarged copies of the square areas marked in white are shown bottom left and bottom right. By applying a standard chromatic adaptation transform CMCCAT2000 [110], the point on the flower arrowed in yellow, bottom left, transforms to a point that is a closer color match to each of the two points arrowed in white, bottom right, than to the correct point arrowed in yellow. The small light-gray rectangular plate at the bottom of the full scene is a reference reflectance surface. The hyperspectral image of the terrace was acquired on October 7, 2003, in Sameiro in the Minho region of Portugal.
Fig. 7.
Fig. 7. Histogram estimates of the relative frequency distributions of the lightness component J, left, the red–green component aC, middle, and the yellow–blue component bC, right, of the CIECAM02 representation of the scene in Fig. 6, top right. The arrows indicate the maximum values of the components, which have very small relative frequencies.

Equations (34)

Equations on this page are rendered with MathJax. Learn more.

ICS(u,v;λ)=IS(u,v;λ)ID(u,v;λ)IF(u,v;λ)ID(u,v;λ).
I˜(u,v;λ0)=t(λ0,λ)I(u,v;λ)dλ.
L^(u,v;λ)=ICS(u,v;λ)l0(λ)ICS(u0,v0;λ).
L^(u,v;λ)=k^0(λ)+k^1(λ)ICS(u,v;λ).
R^(u,v;λ)=ICS(u,v;λ)r0(λ)ICS(u0,v0;λ).
R^(u,v;λ)=k^0(λ)+k^1(λ)ICS(u,v;λ).
E(λ)=l0(λ)/r0(λ).
L(u,v;λ)=E(λ)R(u,v;λ).
L(u,v;λ)=2πE(θ,ϕ;u,v;λ)R(θ,ϕ;u,v;λ)dω,
E(θ,ϕ;u,v;λ)E(θ,ϕ;u,v)E(λ).
L(u,v;λ)E(λ)2πE(θ,ϕ;u,v)R(θ,ϕ;u,v;λ)dω,
L˜2(u,v;λ)=E2(λ)R1(u,v;λ).
X(u,v)=kL(u,v;λ)x¯(λ)dλ,Y(u,v)=kL(u,v;λ)y¯(λ)dλ,Z(u,v)=kL(u,v;λ)z¯(λ)dλ,
L*=116f(Y/Yt)16,a*=500[f(X/Xt)f(Y/Yt)],b*=200[f(Y/Yt)f(Z/Zt)],
f(r)={r1/3ifr>(6/29)3;(841/108)r+4/29otherwise.
[RGB]=[3.24061.53720.49860.96891.87580.04150.05570.20401.0570][XYZ].
R=R0.4,G=G0.4,B=B0.4.
Rc=min{R,c}/c,Gc=min{G,c}/c,Bc=min{B,c}/c.
qL=L(λ)SL(λ)dλ,qM=L(λ)SM(λ)dλ,qS=L(λ)SS(λ)dλ.
[rArRGrYB]=[0.8870.4610.00090.460.880.010.0040.010.99][qLqMqS].
[rL#rM#rS#]=[2.461.980.1000.581.520.140.070.131.0][qLqMqS].
[rL#rM#rS#]=[10.9310.0660.25910.1560.0030.0351][qLqMqS].
N=V(ΔEthr)3.
h(A)=f(a)logf(a)da.
h(A)=1Vlog1Vda=logV,
2h(A)=V.
I(A;B)=h(A)+h(B)h(A,B).
N=2I(A;B).
I(A;B)=h(A)h(W).
I(A;B)=log2h(A)log(ΔEthr)3=log[2h(A)(ΔEthr)3].
N=2h(A)(ΔEthr)3.
N=2I(A1;A2).
I(A1;B)<I(A1;A2).
N=2I(A1;B),

Metrics