Abstract

Many types of RGBW color filter array (CFA) have been proposed for various purposes. Most studies utilize white pixel intensity for improving the signal-to-noise ratio of the image and demosaicing the image, but we note that the white pixel intensity can also be utilized to improve color reproduction. In this paper, we propose a color reproduction pipeline for RGBW CFA sensors based on a fast, accurate, and hardware-friendly gray pixel detection using white pixel intensity. The proposed color reproduction pipeline was tested on a dataset captured from an OPA sensor which has RGBW CFA. Experimental results show that the proposed pipeline estimates the illumination more accurately and preserves the achromatic color better than conventional methods which do not use white pixel intensity.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. R. H. Kröger, “Anti-aliasing in image recording and display hardware: lessons from nature,” J. Opt. A: Pure Appl. Opt. 6(8), 743–748 (2004).
    [Crossref]
  2. R. Lukac and K. N. Plataniotis, “Color filter arrays: Design and performance analysis,” IEEE Trans. Consumer Electronics 51(4), 1260–1267 (2005).
    [Crossref]
  3. Y. Monno, S. Kikuchi, M. Tanaka, and M. Okutomi, “A practical one-shot multispectral imaging system using a single image sensor,” IEEE Trans. Image Process. 24(10), 3048–3059 (2015).
    [Crossref]
  4. J. Couillaud, A. Horé, and D. Ziou, “Nature-inspired color-filter array for enhancing the quality of images,” J. Opt. Soc. Am. A 29(8), 1580–1587 (2012).
    [Crossref]
  5. B. E. Bayer, “Color imaging array,” U.S. patent 3,971,065 (1976).
  6. I. Hirota, “Solid-state imaging device, method for processing signal of solid-state imaging device, and imaging apparatus,” U.S. patent 8,436,925 (2013).
  7. J. T. Compton and J. F. Hamilton Jr, “Image sensor with improved light sensitivity,” U.S. patent 8,139,130 (2005).
  8. H. Honda, Y. Iida, G. Itoh, Y. Egawa, and H. Seki, “A novel Bayer-like WRGB color filter array for CMOS image sensors,” in Human Vision and Electronic Imaging XII (2007), p. 64921J.
  9. Y. Kwak, J. Park, and D.-S. Park, “Generating vivid colors on red-green-blue-white electonic-paper display,” Appl. Opt. 47(25), 4491–4500 (2008).
    [Crossref]
  10. Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
    [Crossref]
  11. S. Jee, K. Song, and M. Kang, “Sensitivity and resolution improvement in RGBW color filter array sensor,” Sensors 18(5), 1647 (2018).
    [Crossref]
  12. B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.
  13. J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
    [Crossref]
  14. B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
    [Crossref]
  15. L. T. Maloney and B. A. Wandell, “Color constancy: a method for recovering surface spectral reflectance,” J. Opt. Soc. Am. A 3(1), 29–33 (1986).
    [Crossref]
  16. G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin Inst. 310(1), 1–26 (1980).
    [Crossref]
  17. G. D. Finlayson and E. Trezzi, “Shades of gray and colour constancy,” in Color and Imaging Conference (2004), pp. 37–41.
  18. J. Van De Weijer, T. Gevers, and A. Gijsenij, “Edge-based color constancy,” IEEE Trans. Image Process. 16(9), 2207–2214 (2007).
    [Crossref]
  19. H. R. V. Joze and M. S. Drew, “Exemplar-based color constancy and multiple illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 36(5), 860–873 (2014).
    [Crossref]
  20. A. Gijsenij and T. Gevers, “Color constancy using natural image statistics and scene semantics,” IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 687–698 (2011).
    [Crossref]
  21. A. Gijsenij, T. Gevers, and J. Van De Weijer, “Generalized gamut mapping using image derivative structures for color constancy,” Int. J. Comput. Vis. 86(2-3), 127–139 (2010).
    [Crossref]
  22. S.-B. Gao, M. Zhang, C.-Y. Li, and Y.-J. Li, “Improving color constancy by discounting the variation of camera spectral sensitivity,” J. Opt. Soc. Am. A 34(8), 1448–1462 (2017).
    [Crossref]
  23. K.-F. Yang, S.-B. Gao, and Y.-J. Li, “Efficient illuminant estimation for color constancy using grey pixels,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 2254–2263.
  24. X. Yang, X. Jin, and J. Zhang, “Improved single-illumination estimation accuracy via redefining the illuminant-invariant descriptor and the grey pixels,” Opt. Express 26(22), 29055–29067 (2018).
    [Crossref]
  25. P.-C. Hung, “Colorimetric calibration in electronic imaging devices using a look-up-table model and interpolations,” J. Electron. Imaging 2(1), 53–62 (1993).
    [Crossref]
  26. J. S. McElvain and W. Gish, “Camera color correction using two-dimensional transforms,” in Color and Imaging Conference (2013), pp. 250–256.
  27. P.-C. Hung, “Color rendition using three-dimensional interpolation,” Imaging Applications in the Work World 0900, 111–115 (1988).
    [Crossref]
  28. H. R. Kang and P. G. Anderson, “Neural network applications to the color scanner and printer calibrations,” J. Electron. Imaging 1(2), 125–136 (1992).
    [Crossref]
  29. V. Cheung, S. Westland, D. Connah, and C. Ripamonti, “A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms,” Color. Technol. 120(1), 19–25 (2004).
    [Crossref]
  30. G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26(1), 76–84 (2001).
    [Crossref]
  31. G. D. Finlayson, M. Mackiewicz, and A. Hurlbert, “Color correction using root-polynomial regression,” IEEE Trans. Image Process. 24(5), 1460–1470 (2015).
    [Crossref]
  32. S. Lim and A. Silverstein, “Spatially varying color correction (SVCC) matrices for reduced noise,” in Color and Imaging Conference (2004), pp. 76–81.
  33. G. D. Finlayson and M. S. Drew, “White-point preserving color correction,” in Color and Imaging Conference (1997), pp. 258–261.
  34. G. D. Finlayson and M. S. Drew, “Constrained least-squares regression in color spaces,” J. Electron. Imaging 6(4), 484–494 (1997).
    [Crossref]
  35. S. A. Shafer, “Using color to separate reflection components,” Color Res. Appl. 10(4), 210–218 (1985).
    [Crossref]
  36. G. J. Klinker, S. A. Shafer, and T. Kanade, “A physical approach to color image understanding,” Int. J. Comput. Vis. 4(1), 7–38 (1990).
    [Crossref]
  37. M. Oren and S. K. Nayar, “Generalization of Lambert's reflectance model,” in Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (1994), pp. 239–246.
  38. W. Shi, C. C. Loy, and X. Tang, “Deep specialized network for illuminant estimation,” in European Conference on Computer Vision (2016), pp. 371–387.
  39. G. D. Finlayson, S. D. Hordley, and P. M. Hubel, “Color by correlation: A simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1209–1221 (2001).
    [Crossref]
  40. A. Gijsenij, T. Gevers, and J. Van De Weijer, “Computational color constancy: Survey and experiments,” IEEE Trans. Image Process. 20(9), 2475–2489 (2011).
    [Crossref]
  41. G. D. Finlayson and R. Zakizadeh, “Reproduction angular error: An improved performance metric for illuminant estimation,” in Proceedings of the British Machine Vision Conference (2014), pp. 1–11.
  42. H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in 2007 IEEE 11th International Conference on Computer Vision (2007), pp. 1–8.
  43. G. D. Finlayson, M. S. Drew, and B. V. Funt, “Color constancy: generalized diagonal transforms suffice,” J. Opt. Soc. Am. A 11(11), 3011–3019 (1994).
    [Crossref]
  44. S. D. Hordley, “Scene illuminant estimation: past, present, and future,” Color Res. Appl. 31(4), 303–314 (2006).
    [Crossref]
  45. A. Gijsenij, T. Gevers, and J. Van De Weijer, “Improving color constancy by photometric edge weighting,” IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 918–929 (2012).
    [Crossref]
  46. S. Kawada, R. Kuroda, and S. Sugawa, “Color reproductivity improvement with additional virtual color filters for WRGB image sensor,” in Color Imaging XVIII (2013), pp. 1–7.
  47. C. Park, K. Song, and M. Kang, “G-channel restoration for RWB CFA with double-exposed W channel,” Sensors 17(2), 293 (2017).
    [Crossref]
  48. P.-H. Su, P.-C. Chen, and H. H. Chen, “Compensation of spectral mismatch to enhance WRGB demosaicking,” in IEEE International Conference on Image Processing (2015), pp. 68–72.
  49. L. J. Van Vliet, I. T. Young, and J. J. Gerbrands, Fundamentals of image processing (Delft University of Technology, 1998).
  50. J. G. Skellam, “The frequency distribution of the difference between two Poisson variates belonging to different populations,” J. Roy. Statist. Soc. (N. S. 109(3), 296 (1946).
    [Crossref]
  51. Y. Hwang, J.-S. Kim, and I.-S. Kweon, “Sensor noise modeling using the Skellam distribution: Application to the color edge detection,” in 2007 IEEE Conference on Computer Vision and Pattern Recognition (2007), pp. 1–8.
  52. J. Vaillant, A. Clouet, and D. Alleysson, “Color correction matrix for sparse RGB-W image sensor without IR cutoff filter,” in Unconventional Optical Imaging (2018), p. 1067704.
  53. P. V. Gehler, C. Rother, A. Blake, T. Minka, and T. Sharp, “Bayesian color constancy revisited,” in 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008), pp. 1–8.
  54. L. Shi and B. Funt, “Re-processed version of the gehler color constancy dataset of 568 images,” Accessed from http://www.cs.sfu.ca/∼colour/data/ (2010).
  55. K. Barnard, L. Martin, B. Funt, and A. Coath, “A data set for color research,” Color Res. Appl. 27(3), 147–151 (2002).
    [Crossref]
  56. F. Ciurea and B. Funt, “A large image database for color constancy research,” in Color and Imaging Conference (2003), pp. 160–164.
  57. D. Cheng, D. K. Prasad, and M. S. Brown, “Illuminant estimation for color constancy: why spatial-domain methods work and the role of the color distribution,” J. Opt. Soc. Am. A 31(5), 1049–1058 (2014).
    [Crossref]

2019 (2)

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

2018 (2)

2017 (2)

2015 (2)

G. D. Finlayson, M. Mackiewicz, and A. Hurlbert, “Color correction using root-polynomial regression,” IEEE Trans. Image Process. 24(5), 1460–1470 (2015).
[Crossref]

Y. Monno, S. Kikuchi, M. Tanaka, and M. Okutomi, “A practical one-shot multispectral imaging system using a single image sensor,” IEEE Trans. Image Process. 24(10), 3048–3059 (2015).
[Crossref]

2014 (2)

H. R. V. Joze and M. S. Drew, “Exemplar-based color constancy and multiple illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 36(5), 860–873 (2014).
[Crossref]

D. Cheng, D. K. Prasad, and M. S. Brown, “Illuminant estimation for color constancy: why spatial-domain methods work and the role of the color distribution,” J. Opt. Soc. Am. A 31(5), 1049–1058 (2014).
[Crossref]

2012 (2)

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Improving color constancy by photometric edge weighting,” IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 918–929 (2012).
[Crossref]

J. Couillaud, A. Horé, and D. Ziou, “Nature-inspired color-filter array for enhancing the quality of images,” J. Opt. Soc. Am. A 29(8), 1580–1587 (2012).
[Crossref]

2011 (2)

A. Gijsenij and T. Gevers, “Color constancy using natural image statistics and scene semantics,” IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 687–698 (2011).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Computational color constancy: Survey and experiments,” IEEE Trans. Image Process. 20(9), 2475–2489 (2011).
[Crossref]

2010 (1)

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Generalized gamut mapping using image derivative structures for color constancy,” Int. J. Comput. Vis. 86(2-3), 127–139 (2010).
[Crossref]

2009 (1)

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

2008 (1)

2007 (1)

J. Van De Weijer, T. Gevers, and A. Gijsenij, “Edge-based color constancy,” IEEE Trans. Image Process. 16(9), 2207–2214 (2007).
[Crossref]

2006 (1)

S. D. Hordley, “Scene illuminant estimation: past, present, and future,” Color Res. Appl. 31(4), 303–314 (2006).
[Crossref]

2005 (1)

R. Lukac and K. N. Plataniotis, “Color filter arrays: Design and performance analysis,” IEEE Trans. Consumer Electronics 51(4), 1260–1267 (2005).
[Crossref]

2004 (2)

R. H. Kröger, “Anti-aliasing in image recording and display hardware: lessons from nature,” J. Opt. A: Pure Appl. Opt. 6(8), 743–748 (2004).
[Crossref]

V. Cheung, S. Westland, D. Connah, and C. Ripamonti, “A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms,” Color. Technol. 120(1), 19–25 (2004).
[Crossref]

2002 (1)

K. Barnard, L. Martin, B. Funt, and A. Coath, “A data set for color research,” Color Res. Appl. 27(3), 147–151 (2002).
[Crossref]

2001 (2)

G. D. Finlayson, S. D. Hordley, and P. M. Hubel, “Color by correlation: A simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1209–1221 (2001).
[Crossref]

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26(1), 76–84 (2001).
[Crossref]

1997 (1)

G. D. Finlayson and M. S. Drew, “Constrained least-squares regression in color spaces,” J. Electron. Imaging 6(4), 484–494 (1997).
[Crossref]

1994 (1)

1993 (1)

P.-C. Hung, “Colorimetric calibration in electronic imaging devices using a look-up-table model and interpolations,” J. Electron. Imaging 2(1), 53–62 (1993).
[Crossref]

1992 (1)

H. R. Kang and P. G. Anderson, “Neural network applications to the color scanner and printer calibrations,” J. Electron. Imaging 1(2), 125–136 (1992).
[Crossref]

1990 (1)

G. J. Klinker, S. A. Shafer, and T. Kanade, “A physical approach to color image understanding,” Int. J. Comput. Vis. 4(1), 7–38 (1990).
[Crossref]

1988 (1)

P.-C. Hung, “Color rendition using three-dimensional interpolation,” Imaging Applications in the Work World 0900, 111–115 (1988).
[Crossref]

1986 (1)

1985 (1)

S. A. Shafer, “Using color to separate reflection components,” Color Res. Appl. 10(4), 210–218 (1985).
[Crossref]

1980 (1)

G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin Inst. 310(1), 1–26 (1980).
[Crossref]

1946 (1)

J. G. Skellam, “The frequency distribution of the difference between two Poisson variates belonging to different populations,” J. Roy. Statist. Soc. (N. S. 109(3), 296 (1946).
[Crossref]

Alleysson, D.

J. Vaillant, A. Clouet, and D. Alleysson, “Color correction matrix for sparse RGB-W image sensor without IR cutoff filter,” in Unconventional Optical Imaging (2018), p. 1067704.

Anderson, P. G.

H. R. Kang and P. G. Anderson, “Neural network applications to the color scanner and printer calibrations,” J. Electron. Imaging 1(2), 125–136 (1992).
[Crossref]

Barnard, K.

K. Barnard, L. Martin, B. Funt, and A. Coath, “A data set for color research,” Color Res. Appl. 27(3), 147–151 (2002).
[Crossref]

Bayer, B. E.

B. E. Bayer, “Color imaging array,” U.S. patent 3,971,065 (1976).

Blake, A.

P. V. Gehler, C. Rother, A. Blake, T. Minka, and T. Sharp, “Bayesian color constancy revisited,” in 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008), pp. 1–8.

Brown, M. S.

Buchsbaum, G.

G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin Inst. 310(1), 1–26 (1980).
[Crossref]

Cao, Y.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Chang, S.

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

Chen, H. H.

P.-H. Su, P.-C. Chen, and H. H. Chen, “Compensation of spectral mismatch to enhance WRGB demosaicking,” in IEEE International Conference on Image Processing (2015), pp. 68–72.

Chen, P.-C.

P.-H. Su, P.-C. Chen, and H. H. Chen, “Compensation of spectral mismatch to enhance WRGB demosaicking,” in IEEE International Conference on Image Processing (2015), pp. 68–72.

Cheng, D.

Cheung, V.

V. Cheung, S. Westland, D. Connah, and C. Ripamonti, “A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms,” Color. Technol. 120(1), 19–25 (2004).
[Crossref]

Choi, B.-S.

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

Chong, H. Y.

H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in 2007 IEEE 11th International Conference on Computer Vision (2007), pp. 1–8.

Ciurea, F.

F. Ciurea and B. Funt, “A large image database for color constancy research,” in Color and Imaging Conference (2003), pp. 160–164.

Clouet, A.

J. Vaillant, A. Clouet, and D. Alleysson, “Color correction matrix for sparse RGB-W image sensor without IR cutoff filter,” in Unconventional Optical Imaging (2018), p. 1067704.

Coath, A.

K. Barnard, L. Martin, B. Funt, and A. Coath, “A data set for color research,” Color Res. Appl. 27(3), 147–151 (2002).
[Crossref]

Compton, J. T.

J. T. Compton and J. F. Hamilton Jr, “Image sensor with improved light sensitivity,” U.S. patent 8,139,130 (2005).

Connah, D.

V. Cheung, S. Westland, D. Connah, and C. Ripamonti, “A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms,” Color. Technol. 120(1), 19–25 (2004).
[Crossref]

Couillaud, J.

Drew, M. S.

H. R. V. Joze and M. S. Drew, “Exemplar-based color constancy and multiple illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 36(5), 860–873 (2014).
[Crossref]

G. D. Finlayson and M. S. Drew, “Constrained least-squares regression in color spaces,” J. Electron. Imaging 6(4), 484–494 (1997).
[Crossref]

G. D. Finlayson, M. S. Drew, and B. V. Funt, “Color constancy: generalized diagonal transforms suffice,” J. Opt. Soc. Am. A 11(11), 3011–3019 (1994).
[Crossref]

G. D. Finlayson and M. S. Drew, “White-point preserving color correction,” in Color and Imaging Conference (1997), pp. 258–261.

Egawa, Y.

H. Honda, Y. Iida, G. Itoh, Y. Egawa, and H. Seki, “A novel Bayer-like WRGB color filter array for CMOS image sensors,” in Human Vision and Electronic Imaging XII (2007), p. 64921J.

Finlayson, G. D.

G. D. Finlayson, M. Mackiewicz, and A. Hurlbert, “Color correction using root-polynomial regression,” IEEE Trans. Image Process. 24(5), 1460–1470 (2015).
[Crossref]

G. D. Finlayson, S. D. Hordley, and P. M. Hubel, “Color by correlation: A simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1209–1221 (2001).
[Crossref]

G. D. Finlayson and M. S. Drew, “Constrained least-squares regression in color spaces,” J. Electron. Imaging 6(4), 484–494 (1997).
[Crossref]

G. D. Finlayson, M. S. Drew, and B. V. Funt, “Color constancy: generalized diagonal transforms suffice,” J. Opt. Soc. Am. A 11(11), 3011–3019 (1994).
[Crossref]

G. D. Finlayson and R. Zakizadeh, “Reproduction angular error: An improved performance metric for illuminant estimation,” in Proceedings of the British Machine Vision Conference (2014), pp. 1–11.

G. D. Finlayson and M. S. Drew, “White-point preserving color correction,” in Color and Imaging Conference (1997), pp. 258–261.

G. D. Finlayson and E. Trezzi, “Shades of gray and colour constancy,” in Color and Imaging Conference (2004), pp. 37–41.

Funt, B.

K. Barnard, L. Martin, B. Funt, and A. Coath, “A data set for color research,” Color Res. Appl. 27(3), 147–151 (2002).
[Crossref]

L. Shi and B. Funt, “Re-processed version of the gehler color constancy dataset of 568 images,” Accessed from http://www.cs.sfu.ca/∼colour/data/ (2010).

F. Ciurea and B. Funt, “A large image database for color constancy research,” in Color and Imaging Conference (2003), pp. 160–164.

Funt, B. V.

Gao, S.-B.

S.-B. Gao, M. Zhang, C.-Y. Li, and Y.-J. Li, “Improving color constancy by discounting the variation of camera spectral sensitivity,” J. Opt. Soc. Am. A 34(8), 1448–1462 (2017).
[Crossref]

K.-F. Yang, S.-B. Gao, and Y.-J. Li, “Efficient illuminant estimation for color constancy using grey pixels,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 2254–2263.

Gehler, P. V.

P. V. Gehler, C. Rother, A. Blake, T. Minka, and T. Sharp, “Bayesian color constancy revisited,” in 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008), pp. 1–8.

Gerbrands, J. J.

L. J. Van Vliet, I. T. Young, and J. J. Gerbrands, Fundamentals of image processing (Delft University of Technology, 1998).

Gevers, T.

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Improving color constancy by photometric edge weighting,” IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 918–929 (2012).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Computational color constancy: Survey and experiments,” IEEE Trans. Image Process. 20(9), 2475–2489 (2011).
[Crossref]

A. Gijsenij and T. Gevers, “Color constancy using natural image statistics and scene semantics,” IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 687–698 (2011).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Generalized gamut mapping using image derivative structures for color constancy,” Int. J. Comput. Vis. 86(2-3), 127–139 (2010).
[Crossref]

J. Van De Weijer, T. Gevers, and A. Gijsenij, “Edge-based color constancy,” IEEE Trans. Image Process. 16(9), 2207–2214 (2007).
[Crossref]

Gijsenij, A.

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Improving color constancy by photometric edge weighting,” IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 918–929 (2012).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Computational color constancy: Survey and experiments,” IEEE Trans. Image Process. 20(9), 2475–2489 (2011).
[Crossref]

A. Gijsenij and T. Gevers, “Color constancy using natural image statistics and scene semantics,” IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 687–698 (2011).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Generalized gamut mapping using image derivative structures for color constancy,” Int. J. Comput. Vis. 86(2-3), 127–139 (2010).
[Crossref]

J. Van De Weijer, T. Gevers, and A. Gijsenij, “Edge-based color constancy,” IEEE Trans. Image Process. 16(9), 2207–2214 (2007).
[Crossref]

Gish, W.

J. S. McElvain and W. Gish, “Camera color correction using two-dimensional transforms,” in Color and Imaging Conference (2013), pp. 250–256.

Gortler, S. J.

H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in 2007 IEEE 11th International Conference on Computer Vision (2007), pp. 1–8.

Hamilton Jr, J. F.

J. T. Compton and J. F. Hamilton Jr, “Image sensor with improved light sensitivity,” U.S. patent 8,139,130 (2005).

Hirota, I.

I. Hirota, “Solid-state imaging device, method for processing signal of solid-state imaging device, and imaging apparatus,” U.S. patent 8,436,925 (2013).

Honda, H.

H. Honda, Y. Iida, G. Itoh, Y. Egawa, and H. Seki, “A novel Bayer-like WRGB color filter array for CMOS image sensors,” in Human Vision and Electronic Imaging XII (2007), p. 64921J.

Hong, G.

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26(1), 76–84 (2001).
[Crossref]

Hordley, S. D.

S. D. Hordley, “Scene illuminant estimation: past, present, and future,” Color Res. Appl. 31(4), 303–314 (2006).
[Crossref]

G. D. Finlayson, S. D. Hordley, and P. M. Hubel, “Color by correlation: A simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1209–1221 (2001).
[Crossref]

Horé, A.

Hubel, P. M.

G. D. Finlayson, S. D. Hordley, and P. M. Hubel, “Color by correlation: A simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1209–1221 (2001).
[Crossref]

Hung, P.-C.

P.-C. Hung, “Colorimetric calibration in electronic imaging devices using a look-up-table model and interpolations,” J. Electron. Imaging 2(1), 53–62 (1993).
[Crossref]

P.-C. Hung, “Color rendition using three-dimensional interpolation,” Imaging Applications in the Work World 0900, 111–115 (1988).
[Crossref]

Hurlbert, A.

G. D. Finlayson, M. Mackiewicz, and A. Hurlbert, “Color correction using root-polynomial regression,” IEEE Trans. Image Process. 24(5), 1460–1470 (2015).
[Crossref]

Hwang, Y.

Y. Hwang, J.-S. Kim, and I.-S. Kweon, “Sensor noise modeling using the Skellam distribution: Application to the color edge detection,” in 2007 IEEE Conference on Computer Vision and Pattern Recognition (2007), pp. 1–8.

Iida, Y.

H. Honda, Y. Iida, G. Itoh, Y. Egawa, and H. Seki, “A novel Bayer-like WRGB color filter array for CMOS image sensors,” in Human Vision and Electronic Imaging XII (2007), p. 64921J.

Itoh, G.

H. Honda, Y. Iida, G. Itoh, Y. Egawa, and H. Seki, “A novel Bayer-like WRGB color filter array for CMOS image sensors,” in Human Vision and Electronic Imaging XII (2007), p. 64921J.

Jee, S.

S. Jee, K. Song, and M. Kang, “Sensitivity and resolution improvement in RGBW color filter array sensor,” Sensors 18(5), 1647 (2018).
[Crossref]

Jin, X.

Joze, H. R. V.

H. R. V. Joze and M. S. Drew, “Exemplar-based color constancy and multiple illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 36(5), 860–873 (2014).
[Crossref]

Kanade, T.

G. J. Klinker, S. A. Shafer, and T. Kanade, “A physical approach to color image understanding,” Int. J. Comput. Vis. 4(1), 7–38 (1990).
[Crossref]

Kang, H. R.

H. R. Kang and P. G. Anderson, “Neural network applications to the color scanner and printer calibrations,” J. Electron. Imaging 1(2), 125–136 (1992).
[Crossref]

Kang, M.

S. Jee, K. Song, and M. Kang, “Sensitivity and resolution improvement in RGBW color filter array sensor,” Sensors 18(5), 1647 (2018).
[Crossref]

C. Park, K. Song, and M. Kang, “G-channel restoration for RWB CFA with double-exposed W channel,” Sensors 17(2), 293 (2017).
[Crossref]

Kawada, S.

S. Kawada, R. Kuroda, and S. Sugawa, “Color reproductivity improvement with additional virtual color filters for WRGB image sensor,” in Color Imaging XVIII (2013), pp. 1–7.

Kikuchi, S.

Y. Monno, S. Kikuchi, M. Tanaka, and M. Okutomi, “A practical one-shot multispectral imaging system using a single image sensor,” IEEE Trans. Image Process. 24(10), 3048–3059 (2015).
[Crossref]

Kim, J.-S.

Y. Hwang, J.-S. Kim, and I.-S. Kweon, “Sensor noise modeling using the Skellam distribution: Application to the color edge detection,” in 2007 IEEE Conference on Computer Vision and Pattern Recognition (2007), pp. 1–8.

Kim, S.-H.

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

Klinker, G. J.

G. J. Klinker, S. A. Shafer, and T. Kanade, “A physical approach to color image understanding,” Int. J. Comput. Vis. 4(1), 7–38 (1990).
[Crossref]

Kröger, R. H.

R. H. Kröger, “Anti-aliasing in image recording and display hardware: lessons from nature,” J. Opt. A: Pure Appl. Opt. 6(8), 743–748 (2004).
[Crossref]

Kuroda, R.

S. Kawada, R. Kuroda, and S. Sugawa, “Color reproductivity improvement with additional virtual color filters for WRGB image sensor,” in Color Imaging XVIII (2013), pp. 1–7.

Kwak, Y.

Kweon, I.-S.

Y. Hwang, J.-S. Kim, and I.-S. Kweon, “Sensor noise modeling using the Skellam distribution: Application to the color edge detection,” in 2007 IEEE Conference on Computer Vision and Pattern Recognition (2007), pp. 1–8.

Lee, J.

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

Lee, S.-J.

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

Li, C.-Y.

Li, Y.-J.

S.-B. Gao, M. Zhang, C.-Y. Li, and Y.-J. Li, “Improving color constancy by discounting the variation of camera spectral sensitivity,” J. Opt. Soc. Am. A 34(8), 1448–1462 (2017).
[Crossref]

K.-F. Yang, S.-B. Gao, and Y.-J. Li, “Efficient illuminant estimation for color constancy using grey pixels,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 2254–2263.

Lim, S.

S. Lim and A. Silverstein, “Spatially varying color correction (SVCC) matrices for reduced noise,” in Color and Imaging Conference (2004), pp. 76–81.

Loy, C. C.

W. Shi, C. C. Loy, and X. Tang, “Deep specialized network for illuminant estimation,” in European Conference on Computer Vision (2016), pp. 371–387.

Lukac, R.

R. Lukac and K. N. Plataniotis, “Color filter arrays: Design and performance analysis,” IEEE Trans. Consumer Electronics 51(4), 1260–1267 (2005).
[Crossref]

Luo, M. R.

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26(1), 76–84 (2001).
[Crossref]

Mackiewicz, M.

G. D. Finlayson, M. Mackiewicz, and A. Hurlbert, “Color correction using root-polynomial regression,” IEEE Trans. Image Process. 24(5), 1460–1470 (2015).
[Crossref]

Maloney, L. T.

Martin, L.

K. Barnard, L. Martin, B. Funt, and A. Coath, “A data set for color research,” Color Res. Appl. 27(3), 147–151 (2002).
[Crossref]

McElvain, J. S.

J. S. McElvain and W. Gish, “Camera color correction using two-dimensional transforms,” in Color and Imaging Conference (2013), pp. 250–256.

Minka, T.

P. V. Gehler, C. Rother, A. Blake, T. Minka, and T. Sharp, “Bayesian color constancy revisited,” in 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008), pp. 1–8.

Monno, Y.

Y. Monno, S. Kikuchi, M. Tanaka, and M. Okutomi, “A practical one-shot multispectral imaging system using a single image sensor,” IEEE Trans. Image Process. 24(10), 3048–3059 (2015).
[Crossref]

Nayar, S. K.

M. Oren and S. K. Nayar, “Generalization of Lambert's reflectance model,” in Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (1994), pp. 239–246.

Okutomi, M.

Y. Monno, S. Kikuchi, M. Tanaka, and M. Okutomi, “A practical one-shot multispectral imaging system using a single image sensor,” IEEE Trans. Image Process. 24(10), 3048–3059 (2015).
[Crossref]

Oren, M.

M. Oren and S. K. Nayar, “Generalization of Lambert's reflectance model,” in Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (1994), pp. 239–246.

Park, C.

C. Park, K. Song, and M. Kang, “G-channel restoration for RWB CFA with double-exposed W channel,” Sensors 17(2), 293 (2017).
[Crossref]

Park, D.-S.

Park, J.

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

Y. Kwak, J. Park, and D.-S. Park, “Generating vivid colors on red-green-blue-white electonic-paper display,” Appl. Opt. 47(25), 4491–4500 (2008).
[Crossref]

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

Peng, J.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Plataniotis, K. N.

R. Lukac and K. N. Plataniotis, “Color filter arrays: Design and performance analysis,” IEEE Trans. Consumer Electronics 51(4), 1260–1267 (2005).
[Crossref]

Prasad, D. K.

Rhodes, P. A.

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26(1), 76–84 (2001).
[Crossref]

Ripamonti, C.

V. Cheung, S. Westland, D. Connah, and C. Ripamonti, “A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms,” Color. Technol. 120(1), 19–25 (2004).
[Crossref]

Rother, C.

P. V. Gehler, C. Rother, A. Blake, T. Minka, and T. Sharp, “Bayesian color constancy revisited,” in 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008), pp. 1–8.

Seki, H.

H. Honda, Y. Iida, G. Itoh, Y. Egawa, and H. Seki, “A novel Bayer-like WRGB color filter array for CMOS image sensors,” in Human Vision and Electronic Imaging XII (2007), p. 64921J.

Seong, D.

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

Shafer, S. A.

G. J. Klinker, S. A. Shafer, and T. Kanade, “A physical approach to color image understanding,” Int. J. Comput. Vis. 4(1), 7–38 (1990).
[Crossref]

S. A. Shafer, “Using color to separate reflection components,” Color Res. Appl. 10(4), 210–218 (1985).
[Crossref]

Sharp, T.

P. V. Gehler, C. Rother, A. Blake, T. Minka, and T. Sharp, “Bayesian color constancy revisited,” in 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008), pp. 1–8.

Shi, L.

L. Shi and B. Funt, “Re-processed version of the gehler color constancy dataset of 568 images,” Accessed from http://www.cs.sfu.ca/∼colour/data/ (2010).

Shi, W.

W. Shi, C. C. Loy, and X. Tang, “Deep specialized network for illuminant estimation,” in European Conference on Computer Vision (2016), pp. 371–387.

Shin, J.-K.

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

Silverstein, A.

S. Lim and A. Silverstein, “Spatially varying color correction (SVCC) matrices for reduced noise,” in Color and Imaging Conference (2004), pp. 76–81.

Skellam, J. G.

J. G. Skellam, “The frequency distribution of the difference between two Poisson variates belonging to different populations,” J. Roy. Statist. Soc. (N. S. 109(3), 296 (1946).
[Crossref]

Song, K.

S. Jee, K. Song, and M. Kang, “Sensitivity and resolution improvement in RGBW color filter array sensor,” Sensors 18(5), 1647 (2018).
[Crossref]

C. Park, K. Song, and M. Kang, “G-channel restoration for RWB CFA with double-exposed W channel,” Sensors 17(2), 293 (2017).
[Crossref]

Su, P.-H.

P.-H. Su, P.-C. Chen, and H. H. Chen, “Compensation of spectral mismatch to enhance WRGB demosaicking,” in IEEE International Conference on Image Processing (2015), pp. 68–72.

Sugawa, S.

S. Kawada, R. Kuroda, and S. Sugawa, “Color reproductivity improvement with additional virtual color filters for WRGB image sensor,” in Color Imaging XVIII (2013), pp. 1–7.

Tanaka, M.

Y. Monno, S. Kikuchi, M. Tanaka, and M. Okutomi, “A practical one-shot multispectral imaging system using a single image sensor,” IEEE Trans. Image Process. 24(10), 3048–3059 (2015).
[Crossref]

Tang, X.

W. Shi, C. C. Loy, and X. Tang, “Deep specialized network for illuminant estimation,” in European Conference on Computer Vision (2016), pp. 371–387.

Trezzi, E.

G. D. Finlayson and E. Trezzi, “Shades of gray and colour constancy,” in Color and Imaging Conference (2004), pp. 37–41.

Vaillant, J.

J. Vaillant, A. Clouet, and D. Alleysson, “Color correction matrix for sparse RGB-W image sensor without IR cutoff filter,” in Unconventional Optical Imaging (2018), p. 1067704.

Van De Weijer, J.

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Improving color constancy by photometric edge weighting,” IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 918–929 (2012).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Computational color constancy: Survey and experiments,” IEEE Trans. Image Process. 20(9), 2475–2489 (2011).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Generalized gamut mapping using image derivative structures for color constancy,” Int. J. Comput. Vis. 86(2-3), 127–139 (2010).
[Crossref]

J. Van De Weijer, T. Gevers, and A. Gijsenij, “Edge-based color constancy,” IEEE Trans. Image Process. 16(9), 2207–2214 (2007).
[Crossref]

Van Vliet, L. J.

L. J. Van Vliet, I. T. Young, and J. J. Gerbrands, Fundamentals of image processing (Delft University of Technology, 1998).

Wandell, B. A.

Wang, J.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Wang, L.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Westland, S.

V. Cheung, S. Westland, D. Connah, and C. Ripamonti, “A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms,” Color. Technol. 120(1), 19–25 (2004).
[Crossref]

Wu, H.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Xiong, Y.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Xu, W.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Xu, Y.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Yang, K.-F.

K.-F. Yang, S.-B. Gao, and Y.-J. Li, “Efficient illuminant estimation for color constancy using grey pixels,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 2254–2263.

Yang, X.

Young, I. T.

L. J. Van Vliet, I. T. Young, and J. J. Gerbrands, Fundamentals of image processing (Delft University of Technology, 1998).

Yu, G.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Zakizadeh, R.

G. D. Finlayson and R. Zakizadeh, “Reproduction angular error: An improved performance metric for illuminant estimation,” in Proceedings of the British Machine Vision Conference (2014), pp. 1–11.

Zhang, J.

Zhang, M.

Zickler, T.

H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in 2007 IEEE 11th International Conference on Computer Vision (2007), pp. 1–8.

Ziou, D.

Zou, J.

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Appl. Opt. (1)

Color Res. Appl. (4)

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26(1), 76–84 (2001).
[Crossref]

S. A. Shafer, “Using color to separate reflection components,” Color Res. Appl. 10(4), 210–218 (1985).
[Crossref]

S. D. Hordley, “Scene illuminant estimation: past, present, and future,” Color Res. Appl. 31(4), 303–314 (2006).
[Crossref]

K. Barnard, L. Martin, B. Funt, and A. Coath, “A data set for color research,” Color Res. Appl. 27(3), 147–151 (2002).
[Crossref]

Color. Technol. (1)

V. Cheung, S. Westland, D. Connah, and C. Ripamonti, “A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms,” Color. Technol. 120(1), 19–25 (2004).
[Crossref]

IEEE Trans. Consumer Electronics (1)

R. Lukac and K. N. Plataniotis, “Color filter arrays: Design and performance analysis,” IEEE Trans. Consumer Electronics 51(4), 1260–1267 (2005).
[Crossref]

IEEE Trans. Image Process. (4)

Y. Monno, S. Kikuchi, M. Tanaka, and M. Okutomi, “A practical one-shot multispectral imaging system using a single image sensor,” IEEE Trans. Image Process. 24(10), 3048–3059 (2015).
[Crossref]

J. Van De Weijer, T. Gevers, and A. Gijsenij, “Edge-based color constancy,” IEEE Trans. Image Process. 16(9), 2207–2214 (2007).
[Crossref]

G. D. Finlayson, M. Mackiewicz, and A. Hurlbert, “Color correction using root-polynomial regression,” IEEE Trans. Image Process. 24(5), 1460–1470 (2015).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Computational color constancy: Survey and experiments,” IEEE Trans. Image Process. 20(9), 2475–2489 (2011).
[Crossref]

IEEE Trans. Pattern Anal. Mach. Intell. (4)

G. D. Finlayson, S. D. Hordley, and P. M. Hubel, “Color by correlation: A simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1209–1221 (2001).
[Crossref]

H. R. V. Joze and M. S. Drew, “Exemplar-based color constancy and multiple illumination,” IEEE Trans. Pattern Anal. Mach. Intell. 36(5), 860–873 (2014).
[Crossref]

A. Gijsenij and T. Gevers, “Color constancy using natural image statistics and scene semantics,” IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 687–698 (2011).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Improving color constancy by photometric edge weighting,” IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 918–929 (2012).
[Crossref]

Imaging Applications in the Work World (1)

P.-C. Hung, “Color rendition using three-dimensional interpolation,” Imaging Applications in the Work World 0900, 111–115 (1988).
[Crossref]

Int. J. Comput. Vis. (2)

G. J. Klinker, S. A. Shafer, and T. Kanade, “A physical approach to color image understanding,” Int. J. Comput. Vis. 4(1), 7–38 (1990).
[Crossref]

A. Gijsenij, T. Gevers, and J. Van De Weijer, “Generalized gamut mapping using image derivative structures for color constancy,” Int. J. Comput. Vis. 86(2-3), 127–139 (2010).
[Crossref]

J. Electron. Imaging (3)

P.-C. Hung, “Colorimetric calibration in electronic imaging devices using a look-up-table model and interpolations,” J. Electron. Imaging 2(1), 53–62 (1993).
[Crossref]

G. D. Finlayson and M. S. Drew, “Constrained least-squares regression in color spaces,” J. Electron. Imaging 6(4), 484–494 (1997).
[Crossref]

H. R. Kang and P. G. Anderson, “Neural network applications to the color scanner and printer calibrations,” J. Electron. Imaging 1(2), 125–136 (1992).
[Crossref]

J. Franklin Inst. (1)

G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin Inst. 310(1), 1–26 (1980).
[Crossref]

J. Opt. A: Pure Appl. Opt. (1)

R. H. Kröger, “Anti-aliasing in image recording and display hardware: lessons from nature,” J. Opt. A: Pure Appl. Opt. 6(8), 743–748 (2004).
[Crossref]

J. Opt. Soc. Am. A (5)

J. Roy. Statist. Soc. (N. S. (1)

J. G. Skellam, “The frequency distribution of the difference between two Poisson variates belonging to different populations,” J. Roy. Statist. Soc. (N. S. 109(3), 296 (1946).
[Crossref]

Opt. Express (1)

Org. Electron. (1)

Y. Xiong, L. Wang, W. Xu, J. Zou, H. Wu, Y. Xu, J. Peng, J. Wang, Y. Cao, and G. Yu, “Performance analysis of PLED based flat panel display with RGBW sub-pixel layout,” Org. Electron. 10(5), 857–862 (2009).
[Crossref]

Sensors (4)

S. Jee, K. Song, and M. Kang, “Sensitivity and resolution improvement in RGBW color filter array sensor,” Sensors 18(5), 1647 (2018).
[Crossref]

J. Lee, B.-S. Choi, S.-H. Kim, J. Lee, J. Lee, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction,” Sensors 19(8), 1823 (2019).
[Crossref]

B.-S. Choi, J. Lee, S.-H. Kim, S. Chang, J. Park, S.-J. Lee, and J.-K. Shin, “Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique,” Sensors 19(3), 472 (2019).
[Crossref]

C. Park, K. Song, and M. Kang, “G-channel restoration for RWB CFA with double-exposed W channel,” Sensors 17(2), 293 (2017).
[Crossref]

Other (22)

P.-H. Su, P.-C. Chen, and H. H. Chen, “Compensation of spectral mismatch to enhance WRGB demosaicking,” in IEEE International Conference on Image Processing (2015), pp. 68–72.

L. J. Van Vliet, I. T. Young, and J. J. Gerbrands, Fundamentals of image processing (Delft University of Technology, 1998).

S. Kawada, R. Kuroda, and S. Sugawa, “Color reproductivity improvement with additional virtual color filters for WRGB image sensor,” in Color Imaging XVIII (2013), pp. 1–7.

Y. Hwang, J.-S. Kim, and I.-S. Kweon, “Sensor noise modeling using the Skellam distribution: Application to the color edge detection,” in 2007 IEEE Conference on Computer Vision and Pattern Recognition (2007), pp. 1–8.

J. Vaillant, A. Clouet, and D. Alleysson, “Color correction matrix for sparse RGB-W image sensor without IR cutoff filter,” in Unconventional Optical Imaging (2018), p. 1067704.

P. V. Gehler, C. Rother, A. Blake, T. Minka, and T. Sharp, “Bayesian color constancy revisited,” in 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008), pp. 1–8.

L. Shi and B. Funt, “Re-processed version of the gehler color constancy dataset of 568 images,” Accessed from http://www.cs.sfu.ca/∼colour/data/ (2010).

F. Ciurea and B. Funt, “A large image database for color constancy research,” in Color and Imaging Conference (2003), pp. 160–164.

B.-S. Choi, S.-H. Kim, J. Lee, D. Seong, J.-K. Shin, S. Chang, J. Park, and S.-J. Lee, “CMOS image sensor for extracting depth information using pixel aperture technique,” in 2018 IEEE International Instrumentation and Measurement Technology Conference (2018), pp. 1–5.

B. E. Bayer, “Color imaging array,” U.S. patent 3,971,065 (1976).

I. Hirota, “Solid-state imaging device, method for processing signal of solid-state imaging device, and imaging apparatus,” U.S. patent 8,436,925 (2013).

J. T. Compton and J. F. Hamilton Jr, “Image sensor with improved light sensitivity,” U.S. patent 8,139,130 (2005).

H. Honda, Y. Iida, G. Itoh, Y. Egawa, and H. Seki, “A novel Bayer-like WRGB color filter array for CMOS image sensors,” in Human Vision and Electronic Imaging XII (2007), p. 64921J.

G. D. Finlayson and E. Trezzi, “Shades of gray and colour constancy,” in Color and Imaging Conference (2004), pp. 37–41.

J. S. McElvain and W. Gish, “Camera color correction using two-dimensional transforms,” in Color and Imaging Conference (2013), pp. 250–256.

K.-F. Yang, S.-B. Gao, and Y.-J. Li, “Efficient illuminant estimation for color constancy using grey pixels,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 2254–2263.

S. Lim and A. Silverstein, “Spatially varying color correction (SVCC) matrices for reduced noise,” in Color and Imaging Conference (2004), pp. 76–81.

G. D. Finlayson and M. S. Drew, “White-point preserving color correction,” in Color and Imaging Conference (1997), pp. 258–261.

G. D. Finlayson and R. Zakizadeh, “Reproduction angular error: An improved performance metric for illuminant estimation,” in Proceedings of the British Machine Vision Conference (2014), pp. 1–11.

H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in 2007 IEEE 11th International Conference on Computer Vision (2007), pp. 1–8.

M. Oren and S. K. Nayar, “Generalization of Lambert's reflectance model,” in Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (1994), pp. 239–246.

W. Shi, C. C. Loy, and X. Tang, “Deep specialized network for illuminant estimation,” in European Conference on Computer Vision (2016), pp. 371–387.

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 (9)

Fig. 1.
Fig. 1. Various color filter array (CFA) patterns. (a) Bayer CFA [5] which is widely used in digital cameras. (b) Sony RGBW CFA [6]. (c) Bayer-like RGBW CFA [8]. (d) Offset pixel aperture (OPA) RGBW CFA [14] whose white pixel is covered with the micro-aperture.
Fig. 2.
Fig. 2. The heat maps of the gray index extracted from various algorithms. (a) Input image of the Macbeth ColorChecker. (b) Ground truth of the gray index (c) Estimated gray index of color constancy using gray pixels [23]. (d) Estimated gray index of improved color constancy using gray pixels [24]. (e) Estimated gray index using $\Delta \log {I_W}(x,y).$ (f) Estimated gray index of the proposed method.
Fig. 3.
Fig. 3. The influence of the variable parameters on the white balance performance in our dataset. (a) Relationship between the angular error and the parameter c of the proposed method. (b) Relationship between the angular error and the parameter n% of the GP15.
Fig. 4.
Fig. 4. Visual results of each algorithm for achromatic color patches of the Macbeth ColorChecker. (a) The results under 6500 K illuminant. (b) The results under 4000 K illuminant. (c) The results under 3500 K illuminant. (d) The results under 2856 K illuminant.
Fig. 5.
Fig. 5. Examples of the of the dataset captured from OPA sensor [14] which has RGBW CFA.
Fig. 6.
Fig. 6. Visual results of each method applied to the image of the dataset. The angular error is displayed at the bottom left of each image.
Fig. 7.
Fig. 7. Comparison of the mean angular error for each patch of the Macbeth ColorChecker.
Fig. 8.
Fig. 8. Visual results of color correction for each patch in Macbeth ColorChecker. The average angular error of the proposed method is the lowest compared with other methods.
Fig. 9.
Fig. 9. Results of each white balance method on images captured on the red solid background. The angular error is displayed at the bottom left of each image.

Tables (4)

Tables Icon

Table 1. The angular errors of each algorithm for the gray patches of the Macbeth ColorCheck under various illuminations.

Tables Icon

Table 2. Performance of various method and the proposed method on the OPA sensor image dataset.

Tables Icon

Table 3. The results of the angular error and the color difference for achromatic color patches and chromatic color patches in the Macbeth ColorChecker.

Tables Icon

Table 4. The results of the color correction methods with and without the proposed adaptive white preserving color correction.

Equations (18)

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

I i ( x , y ) = m b ( x , y ) E ( λ ) S i ( λ ) R b ( x , y , λ ) d λ + m s ( x , y ) E ( λ ) S i ( λ ) R s ( x , y , λ ) d λ ,
I i ( x , y ) = m ( x , y ) E ( λ ) S i ( λ ) R ( x , y , λ ) d λ ,
I i ( x , y ) = E i ( x , y ) R i ( x , y ) ,
log I i ( x , y ) = log ( E i ( x , y ) R i ( x , y ) ) = log E i ( x , y ) + log R i ( x , y ) .
Δ log I W ( x , y ) = | log I W ( x , y ) log I W ( x , y ) | = | log R W ( x , y ) log R W ( x , y ) | .
I W ( x , y ) = k ^ R I R ( x , y ) + k ^ G I G ( x , y ) + k ^ B I B ( x , y ) + k ^ O ,
Δ I W ( x , y ) = I W ( x , y ) I W ( x , y ) .
f ( k ; μ 1 , μ 2 ) = e ( μ 1 + μ 2 ) ( μ 1 μ 2 ) k 2 I k ( 2 μ 1 μ 2 ) ,
μ s = μ 1 μ 2 ,
σ s = μ 1 + μ 2 .
G I ( x , y ) = { 1 | Δ I W ( x , y ) | c σ s if Δ I W ( x , y ) < c σ s 0 otherwise ,
G I ( x , y ) = A F 5 { G I ( x , y ) } ,
e j = 1 N x , y I j ( x , y ) G I ( x , y ) , j { R , G , B } ,
I j W B ( x , y ) = I j ( x , y ) e R + e G + e B 3 e j , j { R , G , B } ,
t = M c ,
M ^ = arg min M | | T M C | | F 2 ,
M w p ^ = w G I M a ^ + ( 1 w G I ) M ^ ,
E r e c = cos 1 ( e g t e e s t | | e g t | | | | e e s t | | ) ,