Abstract

The optimal spectral profiles of lighting for naturalness, individual preference, and chromatic diversity were estimated with psychophysical experiments in which observers selected illuminants from a set of metamers of D65 to render outdoor and indoor scenes. For naturalness, the illuminant selected was more spectrally structured than daylight and had a low color rendering index. For preference, the illuminant was similar but produced colors a little more saturated. For chromatic diversity, the spectrum was much more structured, with clearly defined peaks in the blue, green, and red spectral regions. These experiments show that light sources with specific structured spectra may have important visual applications in lighting.

© 2012 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. M. A. Webster and D. I. A. MacLeod, “Visual adaptation and face perception,” Philos. Trans. R. Soc. B 366, 1702–1725 (2011).
  2. M. A. Webster and D. Leonard, “Adaptation and perceptual norms in color vision,” J. Opt. Soc. Am. A 25, 2817–2825 (2008).
  3. H. E. Smithson, “Sensory, computational and cognitive components of human colour constancy,” Philos. Trans. R. Soc. B 360, 1329–1346 (2005).
  4. D. H. Foster, “Color constancy,” Vis. Res. 51, 674–700(2011).
    [CrossRef]
  5. M. F. Delgado, C. W. Dirk, J. Druzik, and N. WestFall, “Lighting the world's treasures: Approaches to safer museum lighting,” Color Res. Appl. 36, 238–254 (2011).
    [CrossRef]
  6. P. D. Pinto, J. M. M. Linhares, and S. M. C. Nascimento, “Correlated color temperature preferred by observers for illumination of artistic paintings,” J. Opt. Soc. Am. A 25, 623–630 (2008).
  7. J. Schanda, ed., Colorimetry: Understanding the CIE System (Wiley, 2007).
  8. X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Lighting Res. Technol. 36, 183–199 (2004).
    [CrossRef]
  9. “A method for assessing the quality of daylight simulators for colorimetry,” CIE 51.2-1999 (Commission Internationale de L’Eclairage, 1999).
  10. “Method of measuring and specifying colour rendering properties of light sources,” CIE 13:3 (Commission Internationale de L’Eclairage, 1995).
  11. P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).
  12. K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Colour appearance rating of familiar real objects,” Color Res. Appl. 36, 192–200 (2011).
    [CrossRef]
  13. E. Mahler, J. J. Ezrati, and F. Vienot, “Testing LED lighting for colour discrimination and colour rendering,” Color Res. Appl. 34, 8–17 (2009).
    [CrossRef]
  14. C. J. Bartleson, “Memory colors of familiar objects,” J. Opt. Soc. Am. 50, 73–77 (1960).
    [CrossRef]
  15. E. A. Fedorovskaya, H. deRidder, and F. J. J. Blommaert, “Chroma variations and perceived quality of color images of natural scenes,” Color Res. Appl. 22, 96–110 (1997).
    [CrossRef]
  16. T. Hansen, M. Olkkonen, S. Walter, and K. R. Gegenfurtner, “Memory modulates color appearance,” Nat. Neurosci. 9, 1367–1368 (2006).
    [CrossRef]
  17. M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: Effects of object shape, texture, and illumination changes,” J. Vis. 8(5), article 13 (2008).
    [CrossRef]
  18. S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24, 52–67 (1999).
    [CrossRef]
  19. P. D. Pinto, J. M. Linhares, J. A. Carvalhal, and S. M. Nascimento, “Psychophysical estimation of the best illumination for appreciation of Renaissance paintings,” Vis. Neurosci. 23, 669–674 (2006).
  20. H. Xu, “Color-rendering capacity of light,” Color Res. Appl. 18, 267–269 (1993).
    [CrossRef]
  21. F. Martínez-Verdú, E. Perales, E. Chorro, D. D. de Fez, V. Viqueir, 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).
  22. M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: A tale of two metrics,” Color Res. Appl. 33, 192–202 (2008).
    [CrossRef]
  23. J. M. M. Linhares, P. A. Pinto, and S. M. C. Nascimento, “Chromatic diversity index—an approach based on natural scenes,” in Proceedings of CGIV2010[Computer Graphics, Imaging and Vision (CGIV) Research Group, 2010]. 978-0-89208-291-9
  24. J. B. Protzman and K. W. Houser, “LEDs for general illumination: The state of the science,” Leukos 3, 121–142 (2006).
  25. D. H. Foster, K. Amano, and S. M. C. Nascimento, “Color constancy in natural scenes explained by global image statistics,” Vis. Neurosci. 23, 341–349 (2006).
  26. P. L. Vora, J. E. Farrell, J. D. Tietz, and D. H. Brainard, “Image capture: Simulation of sensor responses from hyperspectral images,” IEEE Trans. Image Process. 10, 307–316 (2001).
    [CrossRef]
  27. G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).
  28. F. J. M. Schmitt, “Method for treatment of metamerism in colorimetry,” J. Opt. Soc. Am. 66, 601–608 (1976).
    [CrossRef]
  29. Munsell Book of Color-Matte Finish Collection (Munsell Color Corporation, 1976).
  30. M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).
  31. R. S. Berns, “The science of digitizing paintings for color-accurate image archives: A review,” J. Imaging Sci. Technol. 45, 305–325 (2001).
  32. I. Juricevic, L. Land, A. Wilkins, and M. A. Webster, “Visual discomfort and natural image statistics,” Perception 39, 884–899 (2010).
    [CrossRef]
  33. A. Wilkins and D. Ayles, “Aversion to contemporary art,” Perception 34, 86 (2005).
    [CrossRef]
  34. 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]
  35. D. J. Field, “Relations between the statistics of natural images and the response properties of cortical cells,” J. Opt. Soc. Am. A 4, 2379–2394 (1987).
    [CrossRef]
  36. G. J. Burton and I. R. Moorhead, “Color and spatial structure in natural scenes.,” Appl. Opt. 26, 157–170 (1987).
    [CrossRef]
  37. W. A. Thornton, “Color-Discrimination Index,” J. Opt. Soc. Am. 62, 191–194 (1972).
    [CrossRef]

2011 (4)

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

M. F. Delgado, C. W. Dirk, J. Druzik, and N. WestFall, “Lighting the world's treasures: Approaches to safer museum lighting,” Color Res. Appl. 36, 238–254 (2011).
[CrossRef]

M. A. Webster and D. I. A. MacLeod, “Visual adaptation and face perception,” Philos. Trans. R. Soc. B 366, 1702–1725 (2011).

K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Colour appearance rating of familiar real objects,” Color Res. Appl. 36, 192–200 (2011).
[CrossRef]

2010 (2)

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).

I. Juricevic, L. Land, A. Wilkins, and M. A. Webster, “Visual discomfort and natural image statistics,” Perception 39, 884–899 (2010).
[CrossRef]

2009 (1)

E. Mahler, J. J. Ezrati, and F. Vienot, “Testing LED lighting for colour discrimination and colour rendering,” Color Res. Appl. 34, 8–17 (2009).
[CrossRef]

2008 (4)

M. A. Webster and D. Leonard, “Adaptation and perceptual norms in color vision,” J. Opt. Soc. Am. A 25, 2817–2825 (2008).

P. D. Pinto, J. M. M. Linhares, and S. M. C. Nascimento, “Correlated color temperature preferred by observers for illumination of artistic paintings,” J. Opt. Soc. Am. A 25, 623–630 (2008).

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: Effects of object shape, texture, and illumination changes,” J. Vis. 8(5), article 13 (2008).
[CrossRef]

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: A tale of two metrics,” Color Res. Appl. 33, 192–202 (2008).
[CrossRef]

2007 (1)

2006 (5)

T. Hansen, M. Olkkonen, S. Walter, and K. R. Gegenfurtner, “Memory modulates color appearance,” Nat. Neurosci. 9, 1367–1368 (2006).
[CrossRef]

P. D. Pinto, J. M. Linhares, J. A. Carvalhal, and S. M. Nascimento, “Psychophysical estimation of the best illumination for appreciation of Renaissance paintings,” Vis. Neurosci. 23, 669–674 (2006).

J. B. Protzman and K. W. Houser, “LEDs for general illumination: The state of the science,” Leukos 3, 121–142 (2006).

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Color constancy in natural scenes explained by global image statistics,” Vis. Neurosci. 23, 341–349 (2006).

M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).

2005 (2)

A. Wilkins and D. Ayles, “Aversion to contemporary art,” Perception 34, 86 (2005).
[CrossRef]

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

2004 (1)

X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Lighting Res. Technol. 36, 183–199 (2004).
[CrossRef]

2001 (2)

P. L. Vora, J. E. Farrell, J. D. Tietz, and D. H. Brainard, “Image capture: Simulation of sensor responses from hyperspectral images,” IEEE Trans. Image Process. 10, 307–316 (2001).
[CrossRef]

R. S. Berns, “The science of digitizing paintings for color-accurate image archives: A review,” J. Imaging Sci. Technol. 45, 305–325 (2001).

1999 (1)

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24, 52–67 (1999).
[CrossRef]

1998 (1)

1997 (1)

E. A. Fedorovskaya, H. deRidder, and F. J. J. Blommaert, “Chroma variations and perceived quality of color images of natural scenes,” Color Res. Appl. 22, 96–110 (1997).
[CrossRef]

1993 (1)

H. Xu, “Color-rendering capacity of light,” Color Res. Appl. 18, 267–269 (1993).
[CrossRef]

1987 (2)

1976 (1)

1972 (1)

1960 (1)

Aldaba, M. A.

M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).

Amano, K.

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Color constancy in natural scenes explained by global image statistics,” Vis. Neurosci. 23, 341–349 (2006).

M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).

Ayles, D.

A. Wilkins and D. Ayles, “Aversion to contemporary art,” Perception 34, 86 (2005).
[CrossRef]

Bartleson, C. J.

Berns, R. S.

R. S. Berns, “The science of digitizing paintings for color-accurate image archives: A review,” J. Imaging Sci. Technol. 45, 305–325 (2001).

Blommaert, F. J. J.

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24, 52–67 (1999).
[CrossRef]

E. A. Fedorovskaya, H. deRidder, and F. J. J. Blommaert, “Chroma variations and perceived quality of color images of natural scenes,” Color Res. Appl. 22, 96–110 (1997).
[CrossRef]

Brainard, D. H.

P. L. Vora, J. E. Farrell, J. D. Tietz, and D. H. Brainard, “Image capture: Simulation of sensor responses from hyperspectral images,” IEEE Trans. Image Process. 10, 307–316 (2001).
[CrossRef]

Brelstaff, G.

Burton, G. J.

Carvalhal, J. A.

P. D. Pinto, J. M. Linhares, J. A. Carvalhal, and S. M. Nascimento, “Psychophysical estimation of the best illumination for appreciation of Renaissance paintings,” Vis. Neurosci. 23, 669–674 (2006).

Chorro, E.

de Fez, D. D.

de Ridder, H.

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24, 52–67 (1999).
[CrossRef]

Deconinck, G.

K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Colour appearance rating of familiar real objects,” Color Res. Appl. 36, 192–200 (2011).
[CrossRef]

Delgado, M. F.

M. F. Delgado, C. W. Dirk, J. Druzik, and N. WestFall, “Lighting the world's treasures: Approaches to safer museum lighting,” Color Res. Appl. 36, 238–254 (2011).
[CrossRef]

deRidder, H.

E. A. Fedorovskaya, H. deRidder, and F. J. J. Blommaert, “Chroma variations and perceived quality of color images of natural scenes,” Color Res. Appl. 22, 96–110 (1997).
[CrossRef]

Dirk, C. W.

M. F. Delgado, C. W. Dirk, J. Druzik, and N. WestFall, “Lighting the world's treasures: Approaches to safer museum lighting,” Color Res. Appl. 36, 238–254 (2011).
[CrossRef]

Druzik, J.

M. F. Delgado, C. W. Dirk, J. Druzik, and N. WestFall, “Lighting the world's treasures: Approaches to safer museum lighting,” Color Res. Appl. 36, 238–254 (2011).
[CrossRef]

Ezrati, J. J.

E. Mahler, J. J. Ezrati, and F. Vienot, “Testing LED lighting for colour discrimination and colour rendering,” Color Res. Appl. 34, 8–17 (2009).
[CrossRef]

Farrell, J. E.

P. L. Vora, J. E. Farrell, J. D. Tietz, and D. H. Brainard, “Image capture: Simulation of sensor responses from hyperspectral images,” IEEE Trans. Image Process. 10, 307–316 (2001).
[CrossRef]

Fedorovskaya, E. A.

E. A. Fedorovskaya, H. deRidder, and F. J. J. Blommaert, “Chroma variations and perceived quality of color images of natural scenes,” Color Res. Appl. 22, 96–110 (1997).
[CrossRef]

Field, D. J.

Foster, D. H.

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

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Color constancy in natural scenes explained by global image statistics,” Vis. Neurosci. 23, 341–349 (2006).

M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).

Freyssinier-Nova, J. P.

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: A tale of two metrics,” Color Res. Appl. 33, 192–202 (2008).
[CrossRef]

Gegenfurtner, K. R.

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: Effects of object shape, texture, and illumination changes,” J. Vis. 8(5), article 13 (2008).
[CrossRef]

T. Hansen, M. Olkkonen, S. Walter, and K. R. Gegenfurtner, “Memory modulates color appearance,” Nat. Neurosci. 9, 1367–1368 (2006).
[CrossRef]

Gilabert, E.

Guo, X.

X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Lighting Res. Technol. 36, 183–199 (2004).
[CrossRef]

Hanselaer, P.

K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Colour appearance rating of familiar real objects,” Color Res. Appl. 36, 192–200 (2011).
[CrossRef]

Hansen, T.

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: Effects of object shape, texture, and illumination changes,” J. Vis. 8(5), article 13 (2008).
[CrossRef]

T. Hansen, M. Olkkonen, S. Walter, and K. R. Gegenfurtner, “Memory modulates color appearance,” Nat. Neurosci. 9, 1367–1368 (2006).
[CrossRef]

Houser, K. W.

J. B. Protzman and K. W. Houser, “LEDs for general illumination: The state of the science,” Leukos 3, 121–142 (2006).

X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Lighting Res. Technol. 36, 183–199 (2004).
[CrossRef]

Juricevic, I.

I. Juricevic, L. Land, A. Wilkins, and M. A. Webster, “Visual discomfort and natural image statistics,” Perception 39, 884–899 (2010).
[CrossRef]

Land, L.

I. Juricevic, L. Land, A. Wilkins, and M. A. Webster, “Visual discomfort and natural image statistics,” Perception 39, 884–899 (2010).
[CrossRef]

Leonard, D.

Linhares, J. M.

P. D. Pinto, J. M. Linhares, J. A. Carvalhal, and S. M. Nascimento, “Psychophysical estimation of the best illumination for appreciation of Renaissance paintings,” Vis. Neurosci. 23, 669–674 (2006).

Linhares, J. M. M.

P. D. Pinto, J. M. M. Linhares, and S. M. C. Nascimento, “Correlated color temperature preferred by observers for illumination of artistic paintings,” J. Opt. Soc. Am. A 25, 623–630 (2008).

M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).

J. M. M. Linhares, P. A. Pinto, and S. M. C. Nascimento, “Chromatic diversity index—an approach based on natural scenes,” in Proceedings of CGIV2010[Computer Graphics, Imaging and Vision (CGIV) Research Group, 2010]. 978-0-89208-291-9

MacLeod, D. I. A.

M. A. Webster and D. I. A. MacLeod, “Visual adaptation and face perception,” Philos. Trans. R. Soc. B 366, 1702–1725 (2011).

Mahler, E.

E. Mahler, J. J. Ezrati, and F. Vienot, “Testing LED lighting for colour discrimination and colour rendering,” Color Res. Appl. 34, 8–17 (2009).
[CrossRef]

Martínez-Verdú, F.

Moorehead, I. R.

Moorhead, I. R.

Nascimento, S. M.

P. D. Pinto, J. M. Linhares, J. A. Carvalhal, and S. M. Nascimento, “Psychophysical estimation of the best illumination for appreciation of Renaissance paintings,” Vis. Neurosci. 23, 669–674 (2006).

Nascimento, S. M. C.

P. D. Pinto, J. M. M. Linhares, and S. M. C. Nascimento, “Correlated color temperature preferred by observers for illumination of artistic paintings,” J. Opt. Soc. Am. A 25, 623–630 (2008).

M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Color constancy in natural scenes explained by global image statistics,” Vis. Neurosci. 23, 341–349 (2006).

J. M. M. Linhares, P. A. Pinto, and S. M. C. Nascimento, “Chromatic diversity index—an approach based on natural scenes,” in Proceedings of CGIV2010[Computer Graphics, Imaging and Vision (CGIV) Research Group, 2010]. 978-0-89208-291-9

Olkkonen, M.

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: Effects of object shape, texture, and illumination changes,” J. Vis. 8(5), article 13 (2008).
[CrossRef]

T. Hansen, M. Olkkonen, S. Walter, and K. R. Gegenfurtner, “Memory modulates color appearance,” Nat. Neurosci. 9, 1367–1368 (2006).
[CrossRef]

Párraga, C. A.

Perales, E.

Pinto, P. A.

J. M. M. Linhares, P. A. Pinto, and S. M. C. Nascimento, “Chromatic diversity index—an approach based on natural scenes,” in Proceedings of CGIV2010[Computer Graphics, Imaging and Vision (CGIV) Research Group, 2010]. 978-0-89208-291-9

Pinto, P. D.

P. D. Pinto, J. M. M. Linhares, and S. M. C. Nascimento, “Correlated color temperature preferred by observers for illumination of artistic paintings,” J. Opt. Soc. Am. A 25, 623–630 (2008).

P. D. Pinto, J. M. Linhares, J. A. Carvalhal, and S. M. Nascimento, “Psychophysical estimation of the best illumination for appreciation of Renaissance paintings,” Vis. Neurosci. 23, 669–674 (2006).

M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).

Pointer, M. R.

K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Colour appearance rating of familiar real objects,” Color Res. Appl. 36, 192–200 (2011).
[CrossRef]

Protzman, J. B.

J. B. Protzman and K. W. Houser, “LEDs for general illumination: The state of the science,” Leukos 3, 121–142 (2006).

Rea, M. S.

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: A tale of two metrics,” Color Res. Appl. 33, 192–202 (2008).
[CrossRef]

Ryckaert, W. R.

K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Colour appearance rating of familiar real objects,” Color Res. Appl. 36, 192–200 (2011).
[CrossRef]

Schmitt, F. J. M.

Smet, K.

K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Colour appearance rating of familiar real objects,” Color Res. Appl. 36, 192–200 (2011).
[CrossRef]

Smithson, H. E.

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

Stiles, W. S.

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

Thornton, W. A.

Tietz, J. D.

P. L. Vora, J. E. Farrell, J. D. Tietz, and D. H. Brainard, “Image capture: Simulation of sensor responses from hyperspectral images,” IEEE Trans. Image Process. 10, 307–316 (2001).
[CrossRef]

Troscianko, T.

van der Burgt, P.

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).

van Kemenade, J.

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).

Vienot, F.

E. Mahler, J. J. Ezrati, and F. Vienot, “Testing LED lighting for colour discrimination and colour rendering,” Color Res. Appl. 34, 8–17 (2009).
[CrossRef]

Viqueir, V.

Vora, P. L.

P. L. Vora, J. E. Farrell, J. D. Tietz, and D. H. Brainard, “Image capture: Simulation of sensor responses from hyperspectral images,” IEEE Trans. Image Process. 10, 307–316 (2001).
[CrossRef]

Walter, S.

T. Hansen, M. Olkkonen, S. Walter, and K. R. Gegenfurtner, “Memory modulates color appearance,” Nat. Neurosci. 9, 1367–1368 (2006).
[CrossRef]

Webster, M. A.

M. A. Webster and D. I. A. MacLeod, “Visual adaptation and face perception,” Philos. Trans. R. Soc. B 366, 1702–1725 (2011).

I. Juricevic, L. Land, A. Wilkins, and M. A. Webster, “Visual discomfort and natural image statistics,” Perception 39, 884–899 (2010).
[CrossRef]

M. A. Webster and D. Leonard, “Adaptation and perceptual norms in color vision,” J. Opt. Soc. Am. A 25, 2817–2825 (2008).

WestFall, N.

M. F. Delgado, C. W. Dirk, J. Druzik, and N. WestFall, “Lighting the world's treasures: Approaches to safer museum lighting,” Color Res. Appl. 36, 238–254 (2011).
[CrossRef]

Wilkins, A.

I. Juricevic, L. Land, A. Wilkins, and M. A. Webster, “Visual discomfort and natural image statistics,” Perception 39, 884–899 (2010).
[CrossRef]

A. Wilkins and D. Ayles, “Aversion to contemporary art,” Perception 34, 86 (2005).
[CrossRef]

Wyszecki, G.

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

Xu, H.

H. Xu, “Color-rendering capacity of light,” Color Res. Appl. 18, 267–269 (1993).
[CrossRef]

Yendrikhovskij, S. N.

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24, 52–67 (1999).
[CrossRef]

Appl. Opt. (1)

Color Res. Appl. (8)

H. Xu, “Color-rendering capacity of light,” Color Res. Appl. 18, 267–269 (1993).
[CrossRef]

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: A tale of two metrics,” Color Res. Appl. 33, 192–202 (2008).
[CrossRef]

M. F. Delgado, C. W. Dirk, J. Druzik, and N. WestFall, “Lighting the world's treasures: Approaches to safer museum lighting,” Color Res. Appl. 36, 238–254 (2011).
[CrossRef]

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).

K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Colour appearance rating of familiar real objects,” Color Res. Appl. 36, 192–200 (2011).
[CrossRef]

E. Mahler, J. J. Ezrati, and F. Vienot, “Testing LED lighting for colour discrimination and colour rendering,” Color Res. Appl. 34, 8–17 (2009).
[CrossRef]

E. A. Fedorovskaya, H. deRidder, and F. J. J. Blommaert, “Chroma variations and perceived quality of color images of natural scenes,” Color Res. Appl. 22, 96–110 (1997).
[CrossRef]

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24, 52–67 (1999).
[CrossRef]

IEEE Trans. Image Process. (1)

P. L. Vora, J. E. Farrell, J. D. Tietz, and D. H. Brainard, “Image capture: Simulation of sensor responses from hyperspectral images,” IEEE Trans. Image Process. 10, 307–316 (2001).
[CrossRef]

J. Imaging Sci. Technol. (1)

R. S. Berns, “The science of digitizing paintings for color-accurate image archives: A review,” J. Imaging Sci. Technol. 45, 305–325 (2001).

J. Opt. Soc. Am. (3)

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

J. Vis. (1)

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: Effects of object shape, texture, and illumination changes,” J. Vis. 8(5), article 13 (2008).
[CrossRef]

Leukos (1)

J. B. Protzman and K. W. Houser, “LEDs for general illumination: The state of the science,” Leukos 3, 121–142 (2006).

Lighting Res. Technol. (1)

X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Lighting Res. Technol. 36, 183–199 (2004).
[CrossRef]

Nat. Neurosci. (1)

T. Hansen, M. Olkkonen, S. Walter, and K. R. Gegenfurtner, “Memory modulates color appearance,” Nat. Neurosci. 9, 1367–1368 (2006).
[CrossRef]

Perception (2)

I. Juricevic, L. Land, A. Wilkins, and M. A. Webster, “Visual discomfort and natural image statistics,” Perception 39, 884–899 (2010).
[CrossRef]

A. Wilkins and D. Ayles, “Aversion to contemporary art,” Perception 34, 86 (2005).
[CrossRef]

Philos. Trans. R. Soc. B (2)

M. A. Webster and D. I. A. MacLeod, “Visual adaptation and face perception,” Philos. Trans. R. Soc. B 366, 1702–1725 (2011).

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

Vis. Neurosci. (3)

P. D. Pinto, J. M. Linhares, J. A. Carvalhal, and S. M. Nascimento, “Psychophysical estimation of the best illumination for appreciation of Renaissance paintings,” Vis. Neurosci. 23, 669–674 (2006).

D. H. Foster, K. Amano, and S. M. C. Nascimento, “Color constancy in natural scenes explained by global image statistics,” Vis. Neurosci. 23, 341–349 (2006).

M. A. Aldaba, J. M. M. Linhares, P. D. Pinto, S. M. C. Nascimento, K. Amano, and D. H. Foster, “Visual sensitivity to color errors in images of natural scenes,” Vis. Neurosci. 23, 555–559 (2006).

Vis. Res. (1)

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

Other (6)

J. Schanda, ed., Colorimetry: Understanding the CIE System (Wiley, 2007).

“A method for assessing the quality of daylight simulators for colorimetry,” CIE 51.2-1999 (Commission Internationale de L’Eclairage, 1999).

“Method of measuring and specifying colour rendering properties of light sources,” CIE 13:3 (Commission Internationale de L’Eclairage, 1995).

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

J. M. M. Linhares, P. A. Pinto, and S. M. C. Nascimento, “Chromatic diversity index—an approach based on natural scenes,” in Proceedings of CGIV2010[Computer Graphics, Imaging and Vision (CGIV) Research Group, 2010]. 978-0-89208-291-9

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

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 (8)

Fig. 1.
Fig. 1.

Color pictures of the 12 scenes tested in the experiments. All images were simulated from hyperspectral data. (1) and (3) were from the image database from Brainard’s laboratory (http://color.psych.upenn.edu/hyperspectral/index.html), the outdoor scenes were from a previously digitized set [25], and the other indoor scenes were obtained in our laboratory with a hyperspectral system similar to the one used for outdoor scenes.

Fig. 2.
Fig. 2.

Spectral power of metamers of D65 with different values of δ, the absolute spectral difference relative to D65, and their colored effects for one of the scenes tested. D65 is the spectrum for δ=0. For illustration and better visualization each spectrum was normalized to unity at maximum power.

Fig. 3.
Fig. 3.

Projection screen and one observer carrying out the experiment at 3 m distance. During the experiment the ambient lights were off.

Fig. 4.
Fig. 4.

Average values of δ computed across scenes and observers for the three conditions of the main experiment (white bars) and of the control experiment (listed bars). Error bars represent the standard error of the mean across scenes averaged for all observers.

Fig. 5.
Fig. 5.

Average illuminant spectra selected by the observers for the three conditions of the main experiment. On the left (a) are represented the spectra for naturalness and for preference. On the right (b) are represented the spectra for naturalness and for maximum chromatic diversity. For reference and comparison the spectrum of D65 is represented in both graphs by the dotted line. Error bars represent the standard error of the mean across scenes averaged for all observers for two of the conditions; for the other condition standard errors were similar.

Fig. 6.
Fig. 6.

CRI and CDI expressed as a function of δ for the set of metamers of D65 tested.

Fig. 7.
Fig. 7.

CRI and CDI averaged across observers and scenes for all the conditions of the experiment. Error bars represent the standard error of the mean across scenes averaged for all observers.

Fig. 8.
Fig. 8.

Average values of δ, CRI, and CDI across observers expressed as a function of the scene number.

Equations (3)

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

fi=1NαjSj,
1Nαj=1.
δi=k=1k=33|D65(λk)fi(λk)|.

Metrics