Abstract

Theoretical and experimental approaches have proposed that color constancy involves a correction related to some average of stimulation over the scene, and some of the studies showed that the average gives greater weight to surrounding bright colors. However, in a natural scene, high-luminance elements do not necessarily carry information about the scene illuminant when the luminance is too high for it to appear as a natural object color. The question is how a surrounding color’s appearance mode influences its contribution to the degree of color constancy. Here the stimuli were simple geometric patterns, and the luminance of surrounding colors was tested over the range beyond the luminosity threshold. Observers performed perceptual achromatic setting on the test patch in order to measure the degree of color constancy and evaluated the surrounding bright colors’ appearance mode. Broadly, our results support the assumption that the visual system counts only the colors in the object-color appearance for color constancy. However, detailed analysis indicated that surrounding colors without a fully natural object-color appearance had some sort of influence on color constancy. Consideration of this contribution of unnatural object color might be important for precise modeling of human color constancy.

© 2014 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. D. H. Foster, “Color constancy,” Vis. Res. 51, 674–700 (2011).
    [CrossRef]
  2. G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin Inst. 310, 1–26 (1980).
    [CrossRef]
  3. E. H. Land, “Recent advances in retinex theory and some implications for cortical computations: color vision and the natural image,” Proc. Natl. Acad. Sci. U.S.A 80, 5163–5169 (1983).
  4. E. H. Land, “Recent advances in retinex theory,” Vis. Res. 26, 7–21 (1986).
    [CrossRef]
  5. M. Brill and G. West, “Contributions to the theory of invariance of color under the condition of varying illumination,” J. Math. Biol. 11, 337–350 (1981).
    [CrossRef]
  6. E. H. Land and J. J. McCann, “Lightness and retinex theory,” J. Opt. Soc. Am. 61, 1–11 (1971).
    [CrossRef]
  7. B. G. Khang and Q. Zaidi, “Illuminant color perception of spectrally filtered spotlights,” J. Vis. 4(9):2, 680–692 (2004).
  8. D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).
  9. K. Barnard, L. Martin, A. Coath, and B. Funt, “A comparison of computational color constancy algorithms—part I: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972–984 (2002).
    [CrossRef]
  10. M. D’Zmura and P. Lennie, “Mechanisms of color constancy,” J. Opt. Soc. Am. A 3, 1662–1672 (1986).
    [CrossRef]
  11. H. C. Lee, “Method for computing the scene-illuminant chromaticity from specular highlights,” J. Opt. Soc. Am. A 3, 1694–1699 (1986).
    [CrossRef]
  12. J. Golz and D. I. A. MacLeod, “Influence of scene statistics on colour constancy,” Nature 415, 637–640 (2002).
    [CrossRef]
  13. K. Uchikawa, K. Fukuda, Y. Kitazawa, and D. I. A. MacLeod, “Estimating illuminant color based on luminance balance of surfaces,” J. Opt. Soc. Am. A 29, A133–A143 (2012).
    [CrossRef]
  14. D. Katz, World of Colour (Kegan Paul, 1935).
  15. H. Uchikawa, K. Uchikawa, and R. M. Boynton, “Influence of achromatic surrounds on categorical color perception of surface colors,” Vis. Res. 29, 881–890 (1989).
    [CrossRef]
  16. F. Bonato and A. L. Gilchrist, “The perception of luminosity on different backgrounds and in different illuminations,” Perception 23, 991–1006 (1994).
    [CrossRef]
  17. J. M. Speigle and D. H. Brainard, “Luminosity thresholds: effects of test chromaticity and ambient illumination,” J. Opt. Soc. Am. A 13, 436–451 (1996).
    [CrossRef]
  18. Y. Yamauchi and K. Uchikawa, “Upper-limit luminance for the surface-color mode appearance,” J. Opt. Soc. Am. A 17, 1933–1941 (2000).
    [CrossRef]
  19. K. Barnard, “Color constancy with fluorescent surfaces,” Proceedings of the IS&T/SID Seventh Color Imaging Conference: Color Science, Systems and Applications (1999), pp. 257–261.
  20. B. Funt, K. Barnard, and L. Martin, “Is machine colour constancy good enough?” Proceedings of the 5th European Conference on Computer Vision (Springer-verlag, 1998), pp. 445–459.
  21. M. Ikeda, Y. Mizokami, S. Nakane, and H. Shinoda, “Color appearance of a patch explained by RVSI for the conditions of various colors of room illumination and of various luminance levels of the patch,” Opt. Rev. 9, 132–139 (2002).
    [CrossRef]
  22. P. Pungrassamee, M. Ikeda, and A. Hansuebsai, “Failure of color constancy for high luminance of a test patch that appears unnatural as an object in a space,” Opt. Rev. 14, 139–144 (2007).
    [CrossRef]
  23. P. Cunthasaksiri, H. Shinoda, and M. Ikeda, “Recognized visual space of illumination: no simultaneous color contrast effect on light source colors,” Color Res. Appl. 31, 184–190 (2006).
    [CrossRef]
  24. J. N. Yang and L. T. Maloney, “Illuminant cues in surface color perception: tests of three candidate cues,” Vis. Res. 41, 2581–2600 (2001).
    [CrossRef]
  25. J. N. Yang and S. K. Shevell, “Stereo disparity improves color constancy,” Vis. Res. 42, 1979–1989 (2002).
    [CrossRef]
  26. A. Stockman, D. I. A. MacLeod, and N. E. Johnson, “Spectral sensitivities of the human cones,” J. Opt. Soc. Am. A 10, 2491–2521 (1993).
    [CrossRef]
  27. 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]
  28. K. Masaoka, “Fast and accurate model for optimal color computation,” Opt. Lett. 35, 2031–2033 (2010).
    [CrossRef]
  29. S. Ishihara, Tests for Colour Blindness: 38 Plates Edition (Handaya, 1996) (in Japanese).
  30. H. Yamaguchi, H. Shinoda, and M. Ikeda, “Brightness in natural environments evaluated using the brightness size of recognized visual space of illumination,” J. Light Vis. Environ. 28, 50–57 (2004).
    [CrossRef]
  31. D. L. MacAdam, “The theory of the maximum visual efficiency of colored materials,” J. Opt. Soc. Am. 25, 361–367 (1935).
    [CrossRef]
  32. D. Wollschläger and B. L. Anderson, “The role of layered scene representations in color appearance,” Curr. Biol. 19, 430–435 (2009).
    [CrossRef]

2012 (1)

2011 (1)

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

2010 (1)

2009 (1)

D. Wollschläger and B. L. Anderson, “The role of layered scene representations in color appearance,” Curr. Biol. 19, 430–435 (2009).
[CrossRef]

2007 (1)

P. Pungrassamee, M. Ikeda, and A. Hansuebsai, “Failure of color constancy for high luminance of a test patch that appears unnatural as an object in a space,” Opt. Rev. 14, 139–144 (2007).
[CrossRef]

2006 (2)

P. Cunthasaksiri, H. Shinoda, and M. Ikeda, “Recognized visual space of illumination: no simultaneous color contrast effect on light source colors,” Color Res. Appl. 31, 184–190 (2006).
[CrossRef]

D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).

2004 (2)

B. G. Khang and Q. Zaidi, “Illuminant color perception of spectrally filtered spotlights,” J. Vis. 4(9):2, 680–692 (2004).

H. Yamaguchi, H. Shinoda, and M. Ikeda, “Brightness in natural environments evaluated using the brightness size of recognized visual space of illumination,” J. Light Vis. Environ. 28, 50–57 (2004).
[CrossRef]

2002 (4)

M. Ikeda, Y. Mizokami, S. Nakane, and H. Shinoda, “Color appearance of a patch explained by RVSI for the conditions of various colors of room illumination and of various luminance levels of the patch,” Opt. Rev. 9, 132–139 (2002).
[CrossRef]

J. N. Yang and S. K. Shevell, “Stereo disparity improves color constancy,” Vis. Res. 42, 1979–1989 (2002).
[CrossRef]

J. Golz and D. I. A. MacLeod, “Influence of scene statistics on colour constancy,” Nature 415, 637–640 (2002).
[CrossRef]

K. Barnard, L. Martin, A. Coath, and B. Funt, “A comparison of computational color constancy algorithms—part I: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972–984 (2002).
[CrossRef]

2001 (1)

J. N. Yang and L. T. Maloney, “Illuminant cues in surface color perception: tests of three candidate cues,” Vis. Res. 41, 2581–2600 (2001).
[CrossRef]

2000 (1)

1996 (1)

1994 (1)

F. Bonato and A. L. Gilchrist, “The perception of luminosity on different backgrounds and in different illuminations,” Perception 23, 991–1006 (1994).
[CrossRef]

1993 (1)

1989 (1)

H. Uchikawa, K. Uchikawa, and R. M. Boynton, “Influence of achromatic surrounds on categorical color perception of surface colors,” Vis. Res. 29, 881–890 (1989).
[CrossRef]

1986 (3)

1983 (1)

E. H. Land, “Recent advances in retinex theory and some implications for cortical computations: color vision and the natural image,” Proc. Natl. Acad. Sci. U.S.A 80, 5163–5169 (1983).

1981 (1)

M. Brill and G. West, “Contributions to the theory of invariance of color under the condition of varying illumination,” J. Math. Biol. 11, 337–350 (1981).
[CrossRef]

1980 (1)

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

1979 (1)

1971 (1)

1935 (1)

Anderson, B. L.

D. Wollschläger and B. L. Anderson, “The role of layered scene representations in color appearance,” Curr. Biol. 19, 430–435 (2009).
[CrossRef]

Barnard, K.

K. Barnard, L. Martin, A. Coath, and B. Funt, “A comparison of computational color constancy algorithms—part I: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972–984 (2002).
[CrossRef]

K. Barnard, “Color constancy with fluorescent surfaces,” Proceedings of the IS&T/SID Seventh Color Imaging Conference: Color Science, Systems and Applications (1999), pp. 257–261.

B. Funt, K. Barnard, and L. Martin, “Is machine colour constancy good enough?” Proceedings of the 5th European Conference on Computer Vision (Springer-verlag, 1998), pp. 445–459.

Bonato, F.

F. Bonato and A. L. Gilchrist, “The perception of luminosity on different backgrounds and in different illuminations,” Perception 23, 991–1006 (1994).
[CrossRef]

Boynton, R. M.

H. Uchikawa, K. Uchikawa, and R. M. Boynton, “Influence of achromatic surrounds on categorical color perception of surface colors,” Vis. Res. 29, 881–890 (1989).
[CrossRef]

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]

Brainard, D. H.

D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).

J. M. Speigle and D. H. Brainard, “Luminosity thresholds: effects of test chromaticity and ambient illumination,” J. Opt. Soc. Am. A 13, 436–451 (1996).
[CrossRef]

Brill, M.

M. Brill and G. West, “Contributions to the theory of invariance of color under the condition of varying illumination,” J. Math. Biol. 11, 337–350 (1981).
[CrossRef]

Buchsbaum, G.

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

Coath, A.

K. Barnard, L. Martin, A. Coath, and B. Funt, “A comparison of computational color constancy algorithms—part I: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972–984 (2002).
[CrossRef]

Cunthasaksiri, P.

P. Cunthasaksiri, H. Shinoda, and M. Ikeda, “Recognized visual space of illumination: no simultaneous color contrast effect on light source colors,” Color Res. Appl. 31, 184–190 (2006).
[CrossRef]

D’Zmura, M.

Delahunt, P. B.

D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).

Foster, D. H.

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

Freeman, W. T.

D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).

Fukuda, K.

Funt, B.

K. Barnard, L. Martin, A. Coath, and B. Funt, “A comparison of computational color constancy algorithms—part I: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972–984 (2002).
[CrossRef]

B. Funt, K. Barnard, and L. Martin, “Is machine colour constancy good enough?” Proceedings of the 5th European Conference on Computer Vision (Springer-verlag, 1998), pp. 445–459.

Gilchrist, A. L.

F. Bonato and A. L. Gilchrist, “The perception of luminosity on different backgrounds and in different illuminations,” Perception 23, 991–1006 (1994).
[CrossRef]

Golz, J.

J. Golz and D. I. A. MacLeod, “Influence of scene statistics on colour constancy,” Nature 415, 637–640 (2002).
[CrossRef]

Hansuebsai, A.

P. Pungrassamee, M. Ikeda, and A. Hansuebsai, “Failure of color constancy for high luminance of a test patch that appears unnatural as an object in a space,” Opt. Rev. 14, 139–144 (2007).
[CrossRef]

Ikeda, M.

P. Pungrassamee, M. Ikeda, and A. Hansuebsai, “Failure of color constancy for high luminance of a test patch that appears unnatural as an object in a space,” Opt. Rev. 14, 139–144 (2007).
[CrossRef]

P. Cunthasaksiri, H. Shinoda, and M. Ikeda, “Recognized visual space of illumination: no simultaneous color contrast effect on light source colors,” Color Res. Appl. 31, 184–190 (2006).
[CrossRef]

H. Yamaguchi, H. Shinoda, and M. Ikeda, “Brightness in natural environments evaluated using the brightness size of recognized visual space of illumination,” J. Light Vis. Environ. 28, 50–57 (2004).
[CrossRef]

M. Ikeda, Y. Mizokami, S. Nakane, and H. Shinoda, “Color appearance of a patch explained by RVSI for the conditions of various colors of room illumination and of various luminance levels of the patch,” Opt. Rev. 9, 132–139 (2002).
[CrossRef]

Ishihara, S.

S. Ishihara, Tests for Colour Blindness: 38 Plates Edition (Handaya, 1996) (in Japanese).

Johnson, N. E.

Katz, D.

D. Katz, World of Colour (Kegan Paul, 1935).

Khang, B. G.

B. G. Khang and Q. Zaidi, “Illuminant color perception of spectrally filtered spotlights,” J. Vis. 4(9):2, 680–692 (2004).

Kitazawa, Y.

Kraft, J. M.

D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).

Land, E. H.

E. H. Land, “Recent advances in retinex theory,” Vis. Res. 26, 7–21 (1986).
[CrossRef]

E. H. Land, “Recent advances in retinex theory and some implications for cortical computations: color vision and the natural image,” Proc. Natl. Acad. Sci. U.S.A 80, 5163–5169 (1983).

E. H. Land and J. J. McCann, “Lightness and retinex theory,” J. Opt. Soc. Am. 61, 1–11 (1971).
[CrossRef]

Lee, H. C.

Lennie, P.

Longère, P.

D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).

MacAdam, D. L.

MacLeod, D. I. A.

Maloney, L. T.

J. N. Yang and L. T. Maloney, “Illuminant cues in surface color perception: tests of three candidate cues,” Vis. Res. 41, 2581–2600 (2001).
[CrossRef]

Martin, L.

K. Barnard, L. Martin, A. Coath, and B. Funt, “A comparison of computational color constancy algorithms—part I: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972–984 (2002).
[CrossRef]

B. Funt, K. Barnard, and L. Martin, “Is machine colour constancy good enough?” Proceedings of the 5th European Conference on Computer Vision (Springer-verlag, 1998), pp. 445–459.

Masaoka, K.

McCann, J. J.

Mizokami, Y.

M. Ikeda, Y. Mizokami, S. Nakane, and H. Shinoda, “Color appearance of a patch explained by RVSI for the conditions of various colors of room illumination and of various luminance levels of the patch,” Opt. Rev. 9, 132–139 (2002).
[CrossRef]

Nakane, S.

M. Ikeda, Y. Mizokami, S. Nakane, and H. Shinoda, “Color appearance of a patch explained by RVSI for the conditions of various colors of room illumination and of various luminance levels of the patch,” Opt. Rev. 9, 132–139 (2002).
[CrossRef]

Pungrassamee, P.

P. Pungrassamee, M. Ikeda, and A. Hansuebsai, “Failure of color constancy for high luminance of a test patch that appears unnatural as an object in a space,” Opt. Rev. 14, 139–144 (2007).
[CrossRef]

Shevell, S. K.

J. N. Yang and S. K. Shevell, “Stereo disparity improves color constancy,” Vis. Res. 42, 1979–1989 (2002).
[CrossRef]

Shinoda, H.

P. Cunthasaksiri, H. Shinoda, and M. Ikeda, “Recognized visual space of illumination: no simultaneous color contrast effect on light source colors,” Color Res. Appl. 31, 184–190 (2006).
[CrossRef]

H. Yamaguchi, H. Shinoda, and M. Ikeda, “Brightness in natural environments evaluated using the brightness size of recognized visual space of illumination,” J. Light Vis. Environ. 28, 50–57 (2004).
[CrossRef]

M. Ikeda, Y. Mizokami, S. Nakane, and H. Shinoda, “Color appearance of a patch explained by RVSI for the conditions of various colors of room illumination and of various luminance levels of the patch,” Opt. Rev. 9, 132–139 (2002).
[CrossRef]

Speigle, J. M.

Stockman, A.

Uchikawa, H.

H. Uchikawa, K. Uchikawa, and R. M. Boynton, “Influence of achromatic surrounds on categorical color perception of surface colors,” Vis. Res. 29, 881–890 (1989).
[CrossRef]

Uchikawa, K.

West, G.

M. Brill and G. West, “Contributions to the theory of invariance of color under the condition of varying illumination,” J. Math. Biol. 11, 337–350 (1981).
[CrossRef]

Wollschläger, D.

D. Wollschläger and B. L. Anderson, “The role of layered scene representations in color appearance,” Curr. Biol. 19, 430–435 (2009).
[CrossRef]

Xiao, B.

D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).

Yamaguchi, H.

H. Yamaguchi, H. Shinoda, and M. Ikeda, “Brightness in natural environments evaluated using the brightness size of recognized visual space of illumination,” J. Light Vis. Environ. 28, 50–57 (2004).
[CrossRef]

Yamauchi, Y.

Yang, J. N.

J. N. Yang and S. K. Shevell, “Stereo disparity improves color constancy,” Vis. Res. 42, 1979–1989 (2002).
[CrossRef]

J. N. Yang and L. T. Maloney, “Illuminant cues in surface color perception: tests of three candidate cues,” Vis. Res. 41, 2581–2600 (2001).
[CrossRef]

Zaidi, Q.

B. G. Khang and Q. Zaidi, “Illuminant color perception of spectrally filtered spotlights,” J. Vis. 4(9):2, 680–692 (2004).

Color Res. Appl. (1)

P. Cunthasaksiri, H. Shinoda, and M. Ikeda, “Recognized visual space of illumination: no simultaneous color contrast effect on light source colors,” Color Res. Appl. 31, 184–190 (2006).
[CrossRef]

Curr. Biol. (1)

D. Wollschläger and B. L. Anderson, “The role of layered scene representations in color appearance,” Curr. Biol. 19, 430–435 (2009).
[CrossRef]

IEEE Trans. Image Process. (1)

K. Barnard, L. Martin, A. Coath, and B. Funt, “A comparison of computational color constancy algorithms—part I: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972–984 (2002).
[CrossRef]

J. Franklin Inst. (1)

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

J. Light Vis. Environ. (1)

H. Yamaguchi, H. Shinoda, and M. Ikeda, “Brightness in natural environments evaluated using the brightness size of recognized visual space of illumination,” J. Light Vis. Environ. 28, 50–57 (2004).
[CrossRef]

J. Math. Biol. (1)

M. Brill and G. West, “Contributions to the theory of invariance of color under the condition of varying illumination,” J. Math. Biol. 11, 337–350 (1981).
[CrossRef]

J. Opt. Soc. Am. (3)

J. Opt. Soc. Am. A (6)

J. Vis. (2)

B. G. Khang and Q. Zaidi, “Illuminant color perception of spectrally filtered spotlights,” J. Vis. 4(9):2, 680–692 (2004).

D. H. Brainard, P. Longère, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao, “Bayesian model of human color constancy,” J. Vis. 6(11):10, 1267–1281 (2006).

Nature (1)

J. Golz and D. I. A. MacLeod, “Influence of scene statistics on colour constancy,” Nature 415, 637–640 (2002).
[CrossRef]

Opt. Lett. (1)

Opt. Rev. (2)

M. Ikeda, Y. Mizokami, S. Nakane, and H. Shinoda, “Color appearance of a patch explained by RVSI for the conditions of various colors of room illumination and of various luminance levels of the patch,” Opt. Rev. 9, 132–139 (2002).
[CrossRef]

P. Pungrassamee, M. Ikeda, and A. Hansuebsai, “Failure of color constancy for high luminance of a test patch that appears unnatural as an object in a space,” Opt. Rev. 14, 139–144 (2007).
[CrossRef]

Perception (1)

F. Bonato and A. L. Gilchrist, “The perception of luminosity on different backgrounds and in different illuminations,” Perception 23, 991–1006 (1994).
[CrossRef]

Proc. Natl. Acad. Sci. U.S.A (1)

E. H. Land, “Recent advances in retinex theory and some implications for cortical computations: color vision and the natural image,” Proc. Natl. Acad. Sci. U.S.A 80, 5163–5169 (1983).

Vis. Res. (5)

E. H. Land, “Recent advances in retinex theory,” Vis. Res. 26, 7–21 (1986).
[CrossRef]

J. N. Yang and L. T. Maloney, “Illuminant cues in surface color perception: tests of three candidate cues,” Vis. Res. 41, 2581–2600 (2001).
[CrossRef]

J. N. Yang and S. K. Shevell, “Stereo disparity improves color constancy,” Vis. Res. 42, 1979–1989 (2002).
[CrossRef]

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

H. Uchikawa, K. Uchikawa, and R. M. Boynton, “Influence of achromatic surrounds on categorical color perception of surface colors,” Vis. Res. 29, 881–890 (1989).
[CrossRef]

Other (4)

S. Ishihara, Tests for Colour Blindness: 38 Plates Edition (Handaya, 1996) (in Japanese).

D. Katz, World of Colour (Kegan Paul, 1935).

K. Barnard, “Color constancy with fluorescent surfaces,” Proceedings of the IS&T/SID Seventh Color Imaging Conference: Color Science, Systems and Applications (1999), pp. 257–261.

B. Funt, K. Barnard, and L. Martin, “Is machine colour constancy good enough?” Proceedings of the 5th European Conference on Computer Vision (Springer-verlag, 1998), pp. 445–459.

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.

Example of the stimulus configuration in 6500KN condition.

Fig. 2.
Fig. 2.

Variations of the luminance condition. The upper panels show the stimuli in the 20,000KR3, 20,000KN, and 20,000KB3 conditions. The lower panels show the stimuli in the 3000KR3, 3000KN, and 3000KB3 conditions.

Fig. 3.
Fig. 3.

(a) Example of the mean of the perceptual achromatic settings in each condition for an observer and (b) its enlargement. The X plots indicate the chromaticity of blackbody radiation (3000, 6500, and 20,000 K). The gray-triangle plot denoted “N” shows the result for the 6500KN condition. The red square and blue circle plots show the results for the 3000 and 20,000 K conditions, respectively. The degree of achromatic point shift for the condition 20,000KB3, for example, was defined as the ratio of “shift 20,000KB3” to “distance from 20,000 to 3000 K”.

Fig. 4.
Fig. 4.

Effect of luminance change on perceptual achromatic point shift for the four subjects. The abscissa is an index to the various luminance increment conditions, and the ordinate is the degree of the perceptual achromatic point shift. The red square and blue circle plots show the results for the 3000 and 20,000 K conditions, respectively. The error bars indicate intra-observer’s standard deviation. The stars beside the plots indicate the conditions in which the curves show an extremum.

Fig. 5.
Fig. 5.

Response ratio of complete-surface-color in the two-forced-choices task in each stimulus condition. The red squares with dashed lines and blue circles with solid lines show the results for the 3000 and 20,000 K conditions, respectively. The open symbols represent the responses for the bright color whose luminance was varied (for example, red for the R1–R3 conditions). The filled symbols for observers KS and TM represent the estimation for the other colors (for example, blue or green for the R1–R3 conditions). The stars beside the plots indicate the condition in which we have obtained an extremum of the achromatic point shift in Fig. 4 for each observer (critical luminance conditions).

Fig. 6.
Fig. 6.

Mean of the observer’s magnitude estimations for the reliability of illuminant-color appearance for each stimulus condition. The red square and blue circle plots show the results for the 3000 and 20,000 K conditions, respectively. The open symbols represent the magnitude estimation for the bright color whose luminance was varied (for example, red for the R1–R3 conditions). The filled symbols for observers KS and TM are the estimation for the other colors (for example, blue or green for the R1–R3 conditions). The error bars indicate intra-observer’s standard deviation. The stars indicate the condition in which we have obtained an extremum of the achromatic point shift in Fig. 4 for each observer (critical luminance conditions).

Fig. 7.
Fig. 7.

Correlation diagram between the observer’s magnitude estimations of illuminant-color appearance and the degree of perceptual achromatic point shift for the 3000KB1,B2,B3,R1,R2,R3 and 20,000KB1,B2,B3,R1,R2,R3 conditions. For the degree of achromatic point shift, we subtracted the data for the 3000KN or 20,000KN condition from the data for each condition shown in Fig. 4. The correlation coefficient is 0.37.

Tables (1)

Tables Icon

Table 1. Luminance and Chromaticity of Surrounding Colors in each Condition Represented in MacLeod–Boynton Color Space [27]

Metrics