Abstract

We tested whether surface specularity alone supports operational color constancy—the ability to discriminate changes in illumination or reflectance. Observers viewed short animations of illuminant or reflectance changes in rendered scenes containing a single spherical surface and were asked to classify the change. Performance improved with increasing specularity, as predicted from regularities in chromatic statistics. Peak performance was impaired by spatial rearrangements of image pixels that disrupted the perception of illuminated surfaces but was maintained with increased surface complexity. The characteristic chromatic transformations that are available with nonzero specularity are useful for operational color constancy, particularly if accompanied by appropriate perceptual organization.

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

Full Article  |  PDF Article
OSA Recommended Articles
Discrimination of spectral reflectance under environmental illumination

Takuma Morimoto and Hannah E. Smithson
J. Opt. Soc. Am. A 35(4) B244-B255 (2018)

Color constancy in variegated scenes: role of low-level mechanisms in discounting illumination changes

Qasim Zaidi, Branka Spehar, and Jeremy DeBonet
J. Opt. Soc. Am. A 14(10) 2608-2621 (1997)

References

  • View by:
  • |
  • |
  • |

  1. M. D’Zmura and P. Lennie, “Mechanisms of color constancy,” J. Opt. Soc. Am. A 3, 1662–1672 (1986).
    [Crossref]
  2. H. C. Lee, “Method for computing the scene-illuminant chromaticity from specular highlights,” J. Opt. Soc. Am. A 3, 1694–1699 (1986).
    [Crossref]
  3. S. A. Shafer, “Using color to separate reflection components,” Color Res. Appl. 10, 210–218 (1985).
    [Crossref]
  4. P. J. Marlow, J. Kim, and B. L. Anderson, “The perception and misperception of specular surface reflectance,” Curr. Biol. 22, 1909–1913 (2012).
    [Crossref]
  5. L. T. Maloney, “Physics-based approaches to modeling surface color perception,” in Color Vision: From Genes to Perception, K. R. Gegenfurtner and L. T. Sharpe, eds. (Cambridge University, 1999), pp. 387–416.
  6. H. E. Smithson, “Sensory, computational and cognitive components of human colour constancy,” Philos. Trans. R. Soc. London 360, 1329–1346 (2005).
    [Crossref]
  7. D. H. Foster, “Color constancy,” Vis. Res. 51, 674–700 (2011).
    [Crossref]
  8. J. L. Dannemiller, “Rank orderings of photoreceptor photon catches from natural objects are nearly illuminant-invariant,” Vis. Res. 33, 131–140 (1993).
    [Crossref]
  9. D. H. Foster and S. M. Nascimento, “Relational colour constancy from invariant cone-excitation ratios,” Proc. R. Soc. B 257, 115–121 (1994).
    [Crossref]
  10. Q. Zaidi, B. Spehar, and J. DeBonet, “Color constancy in variegated scenes: role of low-level mechanisms in discounting illumination changes,” J. Opt. Soc. Am. A 14, 2608–2621 (1997).
    [Crossref]
  11. S. M. C. Nascimento, F. P. Ferreira, and D. H. Foster, “Statistics of spatial cone-excitation ratios in natural scenes,” J. Opt. Soc. Am. A 19, 1484–1490 (2002).
    [Crossref]
  12. A. C. Hurlbert, “Computational models of color constancy,” in Perceptual Constancy: Why Things Look as They Do, V. Walsh and J. Kulikowski, eds. (Cambridge University, 1998), pp. 283–322.
  13. 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]
  14. B. J. Craven and D. H. Foster, “An operational approach to color constancy,” Vis. Res. 32, 1359–1366 (1992).
    [Crossref]
  15. G. J. Ward, “Measuring and modeling anisotropic reflection,” in ACM SIGGRAPH Computer Graphics (1992), Vol. 26, pp. 265–272.
  16. G. Ward Larson and R. A. Shakespere, Rendering with Radiance (Morgan Kaufmann, 1998).
  17. D. I. MacLeod and R. M. Boynton, “Chromaticity diagram showing cone excitation by stimuli of equal luminance,” J. Opt. Soc. Am. 69, 1183–1186 (1979).
    [Crossref]
  18. A. Stockman and L. T. Sharpe, “The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype,” Vis. Res. 40, 1711–1737 (2000).
    [Crossref]
  19. A. Stockman, L. T. Sharpe, and C. Fach, “The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches,” Vis. Res. 39, 2901–2927 (1999).
    [Crossref]
  20. L. T. Sharpe, A. Stockman, W. Jagla, and H. Jägle, “A luminous efficiency function, V*(λ), for daylight adaptation,” J. Vis. 5(11), 948–968 (2005).
    [Crossref]
  21. K. J. Linnell and D. H. Foster, “Dependence of relational colour constancy on the extraction of a transient signal,” Perception 25, 221–228 (1996).
    [Crossref]
  22. H. Boyaci, K. Doerschner, and L. T. Maloney, “Perceived surface color in binocularly viewed scenes with two light sources differing in chromaticity,” J. Vis. 4(9), 664–679 (2004).
    [Crossref]
  23. H. Boyaci, K. Doerschner, J. L. Snyder, and L. T. Maloney, “Surface color perception in three-dimensional scenes,” Vis. Neurosci. 23, 311–321 (2006).
  24. K. Doerschner, H. Boyaci, and L. T. Maloney, “Testing limits on matte surface color perception in three-dimensional scenes with complex light fields,” Vis. Res. 47, 3409–3423 (2007).
    [Crossref]
  25. B. Xiao, B. Hurst, L. MacIntyre, and D. H. Brainard, “The color constancy of three-dimensional objects,” J. Vis. 12(4):6, 1–15 (2012).
    [Crossref]
  26. B. Xiao and D. H. Brainard, “Surface gloss and color perception of 3D objects,” Vis. Neurosci. 25, 371–385 (2008).
  27. M. Olkkonen and D. H. Brainard, “Perceived glossiness and lightness under real-world illumination,” J. Vis. 10(9):5, 1–19 (2010).
    [Crossref]
  28. M. Hedrich, M. Bloj, and A. I. Ruppertsberg, “Color constancy improves for real 3D objects,” J. Vis. 9(4):16 (2009).
    [Crossref]
  29. A. Werner, “The influence of depth segmentation on colour constancy,” Perception 35, 1171–1184 (2006).
    [Crossref]
  30. V. M. N. de Almeida, P. T. Fiadeiro, and S. M. C. Nascimento, “Effect of scene dimensionality on colour constancy with real three-dimensional scenes and objects,” Perception 39, 770–779 (2010).
    [Crossref]
  31. K. Amano, D. H. Foster, and S. M. C. Nascimento, “Relational colour constancy across different depth planes,” Perception 31, 65 (2002).
  32. J. Granzier, R. Vergne, and K. Gegenfurtner, “The effects of surface gloss and roughness on color constancy for real 3-D objects,” J. Vis. 14(2):16, 1–20 (2014).
    [Crossref]
  33. E. H. Land and J. J. McCann, “Lightness and retinex theory,” J. Opt. Soc. Am. 61, 1–11 (1971).
    [Crossref]
  34. A. Blake and H. Bülthoff, “Does the brain know the physics of specular reflection?” Nature 343, 165–168 (1990).
    [Crossref]
  35. J. N. Yang and S. K. Shevell, “Stereo disparity improves color constancy,” Vis. Res. 42, 1979–1989 (2002).
    [Crossref]
  36. 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]
  37. G. J. Ward, “The RADIANCE lighting simulation and rendering system,” in Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '94) (ACM, 1994), pp. 459–472.
  38. B. S. Heasly, N. P. Cottaris, D. P. Lichtman, B. Xiao, and D. H. Brainard, “RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research,” J. Vis. 14(2):6, 1–22 (2014).
    [Crossref]
  39. A. I. Ruppertsberg and M. Bloj, “Rendering complex scenes for psychophysics using RADIANCE: how accurate can you get?” J. Opt. Soc. Am. A 23, 759–768 (2006).
    [Crossref]
  40. H. Smithson and Q. Zaidi, “Colour constancy in context: roles for local adaptation and levels of reference,” J. Vis. 4(9), 693–710 (2004).
    [Crossref]
  41. W. L. Martinez and A. R. Martinez, Computational Statistics Handbook with MATLAB, 1st ed. (Chapman and Hall/CRC, 2002).
  42. R. J. Lee, K. A. Dawson, and H. E. Smithson, “Slow updating of the achromatic point after a change in illumination,” J. Vis. 12(1):19, 1–22 (2012).
    [Crossref]
  43. R. J. Lee and H. E. Smithson, “Context-dependent judgments of color that might allow color constancy in scenes with multiple regions of illumination,” J. Opt. Soc. Am. A 29, A247–A257 (2012).
  44. J. A. Schirillo and S. K. Shevell, “Role of perceptual organization in chromatic induction,” J. Opt. Soc. Am. A 17, 244–254 (2000).
    [Crossref]
  45. M. G. Bloj, D. Kersten, and A. C. Hurlbert, “Perception of three-dimensional shape influences colour perception through mutual illumination,” Nature 402, 877–879 (1999).
  46. I. S. Kerrigan and W. J. Adams, “Highlights, disparity, and perceived gloss with convex and concave surfaces,” J. Vis. 13(1):9, 1–10 (2013).
    [Crossref]
  47. D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).
  48. S. W. J. Mooney and B. L. Anderson, “Specular image structure modulates the perception of three-dimensional shape,” Curr. Biol. 24, 2737–2742 (2014).
    [Crossref]

2014 (3)

J. Granzier, R. Vergne, and K. Gegenfurtner, “The effects of surface gloss and roughness on color constancy for real 3-D objects,” J. Vis. 14(2):16, 1–20 (2014).
[Crossref]

B. S. Heasly, N. P. Cottaris, D. P. Lichtman, B. Xiao, and D. H. Brainard, “RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research,” J. Vis. 14(2):6, 1–22 (2014).
[Crossref]

S. W. J. Mooney and B. L. Anderson, “Specular image structure modulates the perception of three-dimensional shape,” Curr. Biol. 24, 2737–2742 (2014).
[Crossref]

2013 (1)

I. S. Kerrigan and W. J. Adams, “Highlights, disparity, and perceived gloss with convex and concave surfaces,” J. Vis. 13(1):9, 1–10 (2013).
[Crossref]

2012 (5)

R. J. Lee, K. A. Dawson, and H. E. Smithson, “Slow updating of the achromatic point after a change in illumination,” J. Vis. 12(1):19, 1–22 (2012).
[Crossref]

R. J. Lee and H. E. Smithson, “Context-dependent judgments of color that might allow color constancy in scenes with multiple regions of illumination,” J. Opt. Soc. Am. A 29, A247–A257 (2012).

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]

B. Xiao, B. Hurst, L. MacIntyre, and D. H. Brainard, “The color constancy of three-dimensional objects,” J. Vis. 12(4):6, 1–15 (2012).
[Crossref]

P. J. Marlow, J. Kim, and B. L. Anderson, “The perception and misperception of specular surface reflectance,” Curr. Biol. 22, 1909–1913 (2012).
[Crossref]

2011 (1)

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

2010 (2)

M. Olkkonen and D. H. Brainard, “Perceived glossiness and lightness under real-world illumination,” J. Vis. 10(9):5, 1–19 (2010).
[Crossref]

V. M. N. de Almeida, P. T. Fiadeiro, and S. M. C. Nascimento, “Effect of scene dimensionality on colour constancy with real three-dimensional scenes and objects,” Perception 39, 770–779 (2010).
[Crossref]

2009 (1)

M. Hedrich, M. Bloj, and A. I. Ruppertsberg, “Color constancy improves for real 3D objects,” J. Vis. 9(4):16 (2009).
[Crossref]

2008 (1)

B. Xiao and D. H. Brainard, “Surface gloss and color perception of 3D objects,” Vis. Neurosci. 25, 371–385 (2008).

2007 (1)

K. Doerschner, H. Boyaci, and L. T. Maloney, “Testing limits on matte surface color perception in three-dimensional scenes with complex light fields,” Vis. Res. 47, 3409–3423 (2007).
[Crossref]

2006 (3)

A. I. Ruppertsberg and M. Bloj, “Rendering complex scenes for psychophysics using RADIANCE: how accurate can you get?” J. Opt. Soc. Am. A 23, 759–768 (2006).
[Crossref]

H. Boyaci, K. Doerschner, J. L. Snyder, and L. T. Maloney, “Surface color perception in three-dimensional scenes,” Vis. Neurosci. 23, 311–321 (2006).

A. Werner, “The influence of depth segmentation on colour constancy,” Perception 35, 1171–1184 (2006).
[Crossref]

2005 (2)

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

L. T. Sharpe, A. Stockman, W. Jagla, and H. Jägle, “A luminous efficiency function, V*(λ), for daylight adaptation,” J. Vis. 5(11), 948–968 (2005).
[Crossref]

2004 (2)

H. Boyaci, K. Doerschner, and L. T. Maloney, “Perceived surface color in binocularly viewed scenes with two light sources differing in chromaticity,” J. Vis. 4(9), 664–679 (2004).
[Crossref]

H. Smithson and Q. Zaidi, “Colour constancy in context: roles for local adaptation and levels of reference,” J. Vis. 4(9), 693–710 (2004).
[Crossref]

2002 (3)

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

K. Amano, D. H. Foster, and S. M. C. Nascimento, “Relational colour constancy across different depth planes,” Perception 31, 65 (2002).

S. M. C. Nascimento, F. P. Ferreira, and D. H. Foster, “Statistics of spatial cone-excitation ratios in natural scenes,” J. Opt. Soc. Am. A 19, 1484–1490 (2002).
[Crossref]

2001 (2)

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]

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

2000 (2)

J. A. Schirillo and S. K. Shevell, “Role of perceptual organization in chromatic induction,” J. Opt. Soc. Am. A 17, 244–254 (2000).
[Crossref]

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

1999 (2)

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

M. G. Bloj, D. Kersten, and A. C. Hurlbert, “Perception of three-dimensional shape influences colour perception through mutual illumination,” Nature 402, 877–879 (1999).

1997 (1)

1996 (1)

K. J. Linnell and D. H. Foster, “Dependence of relational colour constancy on the extraction of a transient signal,” Perception 25, 221–228 (1996).
[Crossref]

1994 (1)

D. H. Foster and S. M. Nascimento, “Relational colour constancy from invariant cone-excitation ratios,” Proc. R. Soc. B 257, 115–121 (1994).
[Crossref]

1993 (1)

J. L. Dannemiller, “Rank orderings of photoreceptor photon catches from natural objects are nearly illuminant-invariant,” Vis. Res. 33, 131–140 (1993).
[Crossref]

1992 (1)

B. J. Craven and D. H. Foster, “An operational approach to color constancy,” Vis. Res. 32, 1359–1366 (1992).
[Crossref]

1990 (1)

A. Blake and H. Bülthoff, “Does the brain know the physics of specular reflection?” Nature 343, 165–168 (1990).
[Crossref]

1986 (2)

1985 (1)

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

1979 (1)

1971 (1)

Adams, W. J.

I. S. Kerrigan and W. J. Adams, “Highlights, disparity, and perceived gloss with convex and concave surfaces,” J. Vis. 13(1):9, 1–10 (2013).
[Crossref]

Amano, K.

K. Amano, D. H. Foster, and S. M. C. Nascimento, “Relational colour constancy across different depth planes,” Perception 31, 65 (2002).

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

Anderson, B. L.

S. W. J. Mooney and B. L. Anderson, “Specular image structure modulates the perception of three-dimensional shape,” Curr. Biol. 24, 2737–2742 (2014).
[Crossref]

P. J. Marlow, J. Kim, and B. L. Anderson, “The perception and misperception of specular surface reflectance,” Curr. Biol. 22, 1909–1913 (2012).
[Crossref]

Arend, L.

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

Blake, A.

A. Blake and H. Bülthoff, “Does the brain know the physics of specular reflection?” Nature 343, 165–168 (1990).
[Crossref]

Bloj, M.

Bloj, M. G.

M. G. Bloj, D. Kersten, and A. C. Hurlbert, “Perception of three-dimensional shape influences colour perception through mutual illumination,” Nature 402, 877–879 (1999).

Boyaci, H.

K. Doerschner, H. Boyaci, and L. T. Maloney, “Testing limits on matte surface color perception in three-dimensional scenes with complex light fields,” Vis. Res. 47, 3409–3423 (2007).
[Crossref]

H. Boyaci, K. Doerschner, J. L. Snyder, and L. T. Maloney, “Surface color perception in three-dimensional scenes,” Vis. Neurosci. 23, 311–321 (2006).

H. Boyaci, K. Doerschner, and L. T. Maloney, “Perceived surface color in binocularly viewed scenes with two light sources differing in chromaticity,” J. Vis. 4(9), 664–679 (2004).
[Crossref]

Boynton, R. M.

Brainard, D. H.

B. S. Heasly, N. P. Cottaris, D. P. Lichtman, B. Xiao, and D. H. Brainard, “RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research,” J. Vis. 14(2):6, 1–22 (2014).
[Crossref]

B. Xiao, B. Hurst, L. MacIntyre, and D. H. Brainard, “The color constancy of three-dimensional objects,” J. Vis. 12(4):6, 1–15 (2012).
[Crossref]

M. Olkkonen and D. H. Brainard, “Perceived glossiness and lightness under real-world illumination,” J. Vis. 10(9):5, 1–19 (2010).
[Crossref]

B. Xiao and D. H. Brainard, “Surface gloss and color perception of 3D objects,” Vis. Neurosci. 25, 371–385 (2008).

Bülthoff, H.

A. Blake and H. Bülthoff, “Does the brain know the physics of specular reflection?” Nature 343, 165–168 (1990).
[Crossref]

Cottaris, N. P.

B. S. Heasly, N. P. Cottaris, D. P. Lichtman, B. Xiao, and D. H. Brainard, “RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research,” J. Vis. 14(2):6, 1–22 (2014).
[Crossref]

Craven, B. J.

B. J. Craven and D. H. Foster, “An operational approach to color constancy,” Vis. Res. 32, 1359–1366 (1992).
[Crossref]

D’Zmura, M.

Dannemiller, J. L.

J. L. Dannemiller, “Rank orderings of photoreceptor photon catches from natural objects are nearly illuminant-invariant,” Vis. Res. 33, 131–140 (1993).
[Crossref]

Dawson, K. A.

R. J. Lee, K. A. Dawson, and H. E. Smithson, “Slow updating of the achromatic point after a change in illumination,” J. Vis. 12(1):19, 1–22 (2012).
[Crossref]

de Almeida, V. M. N.

V. M. N. de Almeida, P. T. Fiadeiro, and S. M. C. Nascimento, “Effect of scene dimensionality on colour constancy with real three-dimensional scenes and objects,” Perception 39, 770–779 (2010).
[Crossref]

DeBonet, J.

Doerschner, K.

K. Doerschner, H. Boyaci, and L. T. Maloney, “Testing limits on matte surface color perception in three-dimensional scenes with complex light fields,” Vis. Res. 47, 3409–3423 (2007).
[Crossref]

H. Boyaci, K. Doerschner, J. L. Snyder, and L. T. Maloney, “Surface color perception in three-dimensional scenes,” Vis. Neurosci. 23, 311–321 (2006).

H. Boyaci, K. Doerschner, and L. T. Maloney, “Perceived surface color in binocularly viewed scenes with two light sources differing in chromaticity,” J. Vis. 4(9), 664–679 (2004).
[Crossref]

Fach, C.

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

Ferreira, F. P.

Fiadeiro, P. T.

V. M. N. de Almeida, P. T. Fiadeiro, and S. M. C. Nascimento, “Effect of scene dimensionality on colour constancy with real three-dimensional scenes and objects,” Perception 39, 770–779 (2010).
[Crossref]

Foster, D. H.

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

K. Amano, D. H. Foster, and S. M. C. Nascimento, “Relational colour constancy across different depth planes,” Perception 31, 65 (2002).

S. M. C. Nascimento, F. P. Ferreira, and D. H. Foster, “Statistics of spatial cone-excitation ratios in natural scenes,” J. Opt. Soc. Am. A 19, 1484–1490 (2002).
[Crossref]

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

K. J. Linnell and D. H. Foster, “Dependence of relational colour constancy on the extraction of a transient signal,” Perception 25, 221–228 (1996).
[Crossref]

D. H. Foster and S. M. Nascimento, “Relational colour constancy from invariant cone-excitation ratios,” Proc. R. Soc. B 257, 115–121 (1994).
[Crossref]

B. J. Craven and D. H. Foster, “An operational approach to color constancy,” Vis. Res. 32, 1359–1366 (1992).
[Crossref]

Foster, J. S.

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

Fukuda, K.

Gegenfurtner, K.

J. Granzier, R. Vergne, and K. Gegenfurtner, “The effects of surface gloss and roughness on color constancy for real 3-D objects,” J. Vis. 14(2):16, 1–20 (2014).
[Crossref]

Granzier, J.

J. Granzier, R. Vergne, and K. Gegenfurtner, “The effects of surface gloss and roughness on color constancy for real 3-D objects,” J. Vis. 14(2):16, 1–20 (2014).
[Crossref]

Heasly, B. S.

B. S. Heasly, N. P. Cottaris, D. P. Lichtman, B. Xiao, and D. H. Brainard, “RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research,” J. Vis. 14(2):6, 1–22 (2014).
[Crossref]

Hedrich, M.

M. Hedrich, M. Bloj, and A. I. Ruppertsberg, “Color constancy improves for real 3D objects,” J. Vis. 9(4):16 (2009).
[Crossref]

Hurlbert, A. C.

M. G. Bloj, D. Kersten, and A. C. Hurlbert, “Perception of three-dimensional shape influences colour perception through mutual illumination,” Nature 402, 877–879 (1999).

A. C. Hurlbert, “Computational models of color constancy,” in Perceptual Constancy: Why Things Look as They Do, V. Walsh and J. Kulikowski, eds. (Cambridge University, 1998), pp. 283–322.

Hurst, B.

B. Xiao, B. Hurst, L. MacIntyre, and D. H. Brainard, “The color constancy of three-dimensional objects,” J. Vis. 12(4):6, 1–15 (2012).
[Crossref]

Jagla, W.

L. T. Sharpe, A. Stockman, W. Jagla, and H. Jägle, “A luminous efficiency function, V*(λ), for daylight adaptation,” J. Vis. 5(11), 948–968 (2005).
[Crossref]

Jägle, H.

L. T. Sharpe, A. Stockman, W. Jagla, and H. Jägle, “A luminous efficiency function, V*(λ), for daylight adaptation,” J. Vis. 5(11), 948–968 (2005).
[Crossref]

Kerrigan, I. S.

I. S. Kerrigan and W. J. Adams, “Highlights, disparity, and perceived gloss with convex and concave surfaces,” J. Vis. 13(1):9, 1–10 (2013).
[Crossref]

Kersten, D.

M. G. Bloj, D. Kersten, and A. C. Hurlbert, “Perception of three-dimensional shape influences colour perception through mutual illumination,” Nature 402, 877–879 (1999).

Kim, J.

P. J. Marlow, J. Kim, and B. L. Anderson, “The perception and misperception of specular surface reflectance,” Curr. Biol. 22, 1909–1913 (2012).
[Crossref]

Kitazawa, Y.

Land, E. H.

Lee, H. C.

Lee, R. J.

R. J. Lee and H. E. Smithson, “Context-dependent judgments of color that might allow color constancy in scenes with multiple regions of illumination,” J. Opt. Soc. Am. A 29, A247–A257 (2012).

R. J. Lee, K. A. Dawson, and H. E. Smithson, “Slow updating of the achromatic point after a change in illumination,” J. Vis. 12(1):19, 1–22 (2012).
[Crossref]

Lennie, P.

Lichtman, D. P.

B. S. Heasly, N. P. Cottaris, D. P. Lichtman, B. Xiao, and D. H. Brainard, “RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research,” J. Vis. 14(2):6, 1–22 (2014).
[Crossref]

Linnell, K. J.

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

K. J. Linnell and D. H. Foster, “Dependence of relational colour constancy on the extraction of a transient signal,” Perception 25, 221–228 (1996).
[Crossref]

MacIntyre, L.

B. Xiao, B. Hurst, L. MacIntyre, and D. H. Brainard, “The color constancy of three-dimensional objects,” J. Vis. 12(4):6, 1–15 (2012).
[Crossref]

MacLeod, D. I.

MacLeod, D. I. A.

Maloney, L. T.

K. Doerschner, H. Boyaci, and L. T. Maloney, “Testing limits on matte surface color perception in three-dimensional scenes with complex light fields,” Vis. Res. 47, 3409–3423 (2007).
[Crossref]

H. Boyaci, K. Doerschner, J. L. Snyder, and L. T. Maloney, “Surface color perception in three-dimensional scenes,” Vis. Neurosci. 23, 311–321 (2006).

H. Boyaci, K. Doerschner, and L. T. Maloney, “Perceived surface color in binocularly viewed scenes with two light sources differing in chromaticity,” J. Vis. 4(9), 664–679 (2004).
[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]

L. T. Maloney, “Physics-based approaches to modeling surface color perception,” in Color Vision: From Genes to Perception, K. R. Gegenfurtner and L. T. Sharpe, eds. (Cambridge University, 1999), pp. 387–416.

Marlow, P. J.

P. J. Marlow, J. Kim, and B. L. Anderson, “The perception and misperception of specular surface reflectance,” Curr. Biol. 22, 1909–1913 (2012).
[Crossref]

Martinez, A. R.

W. L. Martinez and A. R. Martinez, Computational Statistics Handbook with MATLAB, 1st ed. (Chapman and Hall/CRC, 2002).

Martinez, W. L.

W. L. Martinez and A. R. Martinez, Computational Statistics Handbook with MATLAB, 1st ed. (Chapman and Hall/CRC, 2002).

McCann, J. J.

Mooney, S. W. J.

S. W. J. Mooney and B. L. Anderson, “Specular image structure modulates the perception of three-dimensional shape,” Curr. Biol. 24, 2737–2742 (2014).
[Crossref]

Nascimento, S. M.

D. H. Foster and S. M. Nascimento, “Relational colour constancy from invariant cone-excitation ratios,” Proc. R. Soc. B 257, 115–121 (1994).
[Crossref]

Nascimento, S. M. C.

V. M. N. de Almeida, P. T. Fiadeiro, and S. M. C. Nascimento, “Effect of scene dimensionality on colour constancy with real three-dimensional scenes and objects,” Perception 39, 770–779 (2010).
[Crossref]

K. Amano, D. H. Foster, and S. M. C. Nascimento, “Relational colour constancy across different depth planes,” Perception 31, 65 (2002).

S. M. C. Nascimento, F. P. Ferreira, and D. H. Foster, “Statistics of spatial cone-excitation ratios in natural scenes,” J. Opt. Soc. Am. A 19, 1484–1490 (2002).
[Crossref]

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

Nieves, J. L.

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

Olkkonen, M.

M. Olkkonen and D. H. Brainard, “Perceived glossiness and lightness under real-world illumination,” J. Vis. 10(9):5, 1–19 (2010).
[Crossref]

Plet, S.

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

Ruppertsberg, A. I.

Schirillo, J. A.

Shafer, S. A.

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

Shakespere, R. A.

G. Ward Larson and R. A. Shakespere, Rendering with Radiance (Morgan Kaufmann, 1998).

Sharpe, L. T.

L. T. Sharpe, A. Stockman, W. Jagla, and H. Jägle, “A luminous efficiency function, V*(λ), for daylight adaptation,” J. Vis. 5(11), 948–968 (2005).
[Crossref]

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

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

Shevell, S. K.

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

J. A. Schirillo and S. K. Shevell, “Role of perceptual organization in chromatic induction,” J. Opt. Soc. Am. A 17, 244–254 (2000).
[Crossref]

Smithson, H.

H. Smithson and Q. Zaidi, “Colour constancy in context: roles for local adaptation and levels of reference,” J. Vis. 4(9), 693–710 (2004).
[Crossref]

Smithson, H. E.

R. J. Lee, K. A. Dawson, and H. E. Smithson, “Slow updating of the achromatic point after a change in illumination,” J. Vis. 12(1):19, 1–22 (2012).
[Crossref]

R. J. Lee and H. E. Smithson, “Context-dependent judgments of color that might allow color constancy in scenes with multiple regions of illumination,” J. Opt. Soc. Am. A 29, A247–A257 (2012).

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

Snyder, J. L.

H. Boyaci, K. Doerschner, J. L. Snyder, and L. T. Maloney, “Surface color perception in three-dimensional scenes,” Vis. Neurosci. 23, 311–321 (2006).

Spehar, B.

Stockman, A.

L. T. Sharpe, A. Stockman, W. Jagla, and H. Jägle, “A luminous efficiency function, V*(λ), for daylight adaptation,” J. Vis. 5(11), 948–968 (2005).
[Crossref]

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

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

Uchikawa, K.

Vergne, R.

J. Granzier, R. Vergne, and K. Gegenfurtner, “The effects of surface gloss and roughness on color constancy for real 3-D objects,” J. Vis. 14(2):16, 1–20 (2014).
[Crossref]

Ward, G. J.

G. J. Ward, “Measuring and modeling anisotropic reflection,” in ACM SIGGRAPH Computer Graphics (1992), Vol. 26, pp. 265–272.

G. J. Ward, “The RADIANCE lighting simulation and rendering system,” in Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '94) (ACM, 1994), pp. 459–472.

Ward Larson, G.

G. Ward Larson and R. A. Shakespere, Rendering with Radiance (Morgan Kaufmann, 1998).

Werner, A.

A. Werner, “The influence of depth segmentation on colour constancy,” Perception 35, 1171–1184 (2006).
[Crossref]

Xiao, B.

B. S. Heasly, N. P. Cottaris, D. P. Lichtman, B. Xiao, and D. H. Brainard, “RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research,” J. Vis. 14(2):6, 1–22 (2014).
[Crossref]

B. Xiao, B. Hurst, L. MacIntyre, and D. H. Brainard, “The color constancy of three-dimensional objects,” J. Vis. 12(4):6, 1–15 (2012).
[Crossref]

B. Xiao and D. H. Brainard, “Surface gloss and color perception of 3D objects,” Vis. Neurosci. 25, 371–385 (2008).

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.

H. Smithson and Q. Zaidi, “Colour constancy in context: roles for local adaptation and levels of reference,” J. Vis. 4(9), 693–710 (2004).
[Crossref]

Q. Zaidi, B. Spehar, and J. DeBonet, “Color constancy in variegated scenes: role of low-level mechanisms in discounting illumination changes,” J. Opt. Soc. Am. A 14, 2608–2621 (1997).
[Crossref]

Color Res. Appl. (1)

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

Curr. Biol. (2)

P. J. Marlow, J. Kim, and B. L. Anderson, “The perception and misperception of specular surface reflectance,” Curr. Biol. 22, 1909–1913 (2012).
[Crossref]

S. W. J. Mooney and B. L. Anderson, “Specular image structure modulates the perception of three-dimensional shape,” Curr. Biol. 24, 2737–2742 (2014).
[Crossref]

J. Opt. Soc. Am. (2)

J. Opt. Soc. Am. A (8)

J. Vis. (10)

B. S. Heasly, N. P. Cottaris, D. P. Lichtman, B. Xiao, and D. H. Brainard, “RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research,” J. Vis. 14(2):6, 1–22 (2014).
[Crossref]

R. J. Lee, K. A. Dawson, and H. E. Smithson, “Slow updating of the achromatic point after a change in illumination,” J. Vis. 12(1):19, 1–22 (2012).
[Crossref]

I. S. Kerrigan and W. J. Adams, “Highlights, disparity, and perceived gloss with convex and concave surfaces,” J. Vis. 13(1):9, 1–10 (2013).
[Crossref]

L. T. Sharpe, A. Stockman, W. Jagla, and H. Jägle, “A luminous efficiency function, V*(λ), for daylight adaptation,” J. Vis. 5(11), 948–968 (2005).
[Crossref]

H. Smithson and Q. Zaidi, “Colour constancy in context: roles for local adaptation and levels of reference,” J. Vis. 4(9), 693–710 (2004).
[Crossref]

J. Granzier, R. Vergne, and K. Gegenfurtner, “The effects of surface gloss and roughness on color constancy for real 3-D objects,” J. Vis. 14(2):16, 1–20 (2014).
[Crossref]

H. Boyaci, K. Doerschner, and L. T. Maloney, “Perceived surface color in binocularly viewed scenes with two light sources differing in chromaticity,” J. Vis. 4(9), 664–679 (2004).
[Crossref]

B. Xiao, B. Hurst, L. MacIntyre, and D. H. Brainard, “The color constancy of three-dimensional objects,” J. Vis. 12(4):6, 1–15 (2012).
[Crossref]

M. Olkkonen and D. H. Brainard, “Perceived glossiness and lightness under real-world illumination,” J. Vis. 10(9):5, 1–19 (2010).
[Crossref]

M. Hedrich, M. Bloj, and A. I. Ruppertsberg, “Color constancy improves for real 3D objects,” J. Vis. 9(4):16 (2009).
[Crossref]

Nature (2)

A. Blake and H. Bülthoff, “Does the brain know the physics of specular reflection?” Nature 343, 165–168 (1990).
[Crossref]

M. G. Bloj, D. Kersten, and A. C. Hurlbert, “Perception of three-dimensional shape influences colour perception through mutual illumination,” Nature 402, 877–879 (1999).

Perception (4)

A. Werner, “The influence of depth segmentation on colour constancy,” Perception 35, 1171–1184 (2006).
[Crossref]

V. M. N. de Almeida, P. T. Fiadeiro, and S. M. C. Nascimento, “Effect of scene dimensionality on colour constancy with real three-dimensional scenes and objects,” Perception 39, 770–779 (2010).
[Crossref]

K. Amano, D. H. Foster, and S. M. C. Nascimento, “Relational colour constancy across different depth planes,” Perception 31, 65 (2002).

K. J. Linnell and D. H. Foster, “Dependence of relational colour constancy on the extraction of a transient signal,” Perception 25, 221–228 (1996).
[Crossref]

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

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

Proc. Natl. Acad. Sci. USA (1)

D. H. Foster, S. M. C. Nascimento, K. Amano, L. Arend, K. J. Linnell, J. L. Nieves, S. Plet, and J. S. Foster, “Parallel detection of violations of color constancy,” Proc. Natl. Acad. Sci. USA 98, 8151–8156 (2001).

Proc. R. Soc. B (1)

D. H. Foster and S. M. Nascimento, “Relational colour constancy from invariant cone-excitation ratios,” Proc. R. Soc. B 257, 115–121 (1994).
[Crossref]

Vis. Neurosci. (2)

B. Xiao and D. H. Brainard, “Surface gloss and color perception of 3D objects,” Vis. Neurosci. 25, 371–385 (2008).

H. Boyaci, K. Doerschner, J. L. Snyder, and L. T. Maloney, “Surface color perception in three-dimensional scenes,” Vis. Neurosci. 23, 311–321 (2006).

Vis. Res. (8)

K. Doerschner, H. Boyaci, and L. T. Maloney, “Testing limits on matte surface color perception in three-dimensional scenes with complex light fields,” Vis. Res. 47, 3409–3423 (2007).
[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]

J. L. Dannemiller, “Rank orderings of photoreceptor photon catches from natural objects are nearly illuminant-invariant,” Vis. Res. 33, 131–140 (1993).
[Crossref]

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

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

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]

B. J. Craven and D. H. Foster, “An operational approach to color constancy,” Vis. Res. 32, 1359–1366 (1992).
[Crossref]

Other (6)

G. J. Ward, “Measuring and modeling anisotropic reflection,” in ACM SIGGRAPH Computer Graphics (1992), Vol. 26, pp. 265–272.

G. Ward Larson and R. A. Shakespere, Rendering with Radiance (Morgan Kaufmann, 1998).

A. C. Hurlbert, “Computational models of color constancy,” in Perceptual Constancy: Why Things Look as They Do, V. Walsh and J. Kulikowski, eds. (Cambridge University, 1998), pp. 283–322.

L. T. Maloney, “Physics-based approaches to modeling surface color perception,” in Color Vision: From Genes to Perception, K. R. Gegenfurtner and L. T. Sharpe, eds. (Cambridge University, 1999), pp. 387–416.

W. L. Martinez and A. R. Martinez, Computational Statistics Handbook with MATLAB, 1st ed. (Chapman and Hall/CRC, 2002).

G. J. Ward, “The RADIANCE lighting simulation and rendering system,” in Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '94) (ACM, 1994), pp. 459–472.

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. Chromaticity distributions from stimulus images, plotted in the MacLeod and Boynton [17] chromaticity diagram (constructed using the Stockman and Sharpe cone fundamentals [18,19] with the S-cone fundamental scaled so that the maximum S / ( L + M ) value of the spectrum locus is 1 and the L- and M-cone fundamentals scaled so that they sum to V * ( λ ) [20]). These are taken from animations of spheres with high specularity. The blue dots show chromaticities from the first frame of the animation, and the red dots show the chromaticities from the final frame. The top and bottom panels show the conditions to be discriminated in an operational constancy task: (top) a change in the spectral reflectance function of the sphere surface, with no change in the illuminant [ I ( λ ) R 1 ( λ ) to I ( λ ) R 2 ( λ ) ]; and (bottom) a change in the spectral power distribution of the illuminant, with no change in the reflectance [ I 1 ( λ ) R ( λ ) to I 2 ( λ ) R ( λ ) ]. The red and blue square symbols plot at the chromaticity of the product of the corresponding illuminant and reflectance functions ( I R ) projected onto the zero-luminance plane, and the + and × symbols plot at the chromaticity of the illuminant ( I ). These I chromaticities have been plotted with reduced luminance since they were never directly viewed and would be outside the range of the plot axes if plotted at their actual luminances. The 2D insets in each plot show the same chromaticity distributions projected onto an isoluminant plane.
Fig. 2.
Fig. 2. Chromaticities of the brightest pixels in our stimulus images, expressed as a proportion of the distance from the chromaticity of the diffuse component ( I R ) to the chromaticity of the illuminant ( I ), for the different specularities and conditions used in our experiments. The left panel shows the distributions for all three conditions of Experiment 1, since they share the same chromatic statistics. The center and right panels show the distributions for the Bumpy and Marbled stimuli, respectively, from Experiment 2. In the right panel, the extra series of gray boxes shows the distributions identified by selecting the center of the highlight, rather than the brightest pixels in the images.
Fig. 3.
Fig. 3. Examples of changes in normalized cone excitations elicited by our stimuli. Only excitations of L cones are shown, but excitations of the M and S cones show similar patterns. In each plot, the L-cone excitation from the first frame is plotted on the abscissa, and the corresponding excitation from the final frame is plotted on the ordinate. Each dot represents a pixel in the animation. The number inside each plot indicates the specularity of the surface in the stimuli: high specularity in the bottom panels and zero in the top panels. The left panels show chromaticities from a reflectance-change stimulus and the right panels show chromaticities from an illuminant-change stimulus. Note that the transformation in an illuminant change is multiplicative but this is not the case for a reflectance change with nonzero specularity (lower left panel).
Fig. 4.
Fig. 4. Examples of images from the stimulus animations used in our experiments. The left two columns show the first and final images from an animation of a reflectance change, while the right two columns show the first and final images from an animation of an illuminant change. To aid comparison of these stimulus types, the reflectance and illuminant for the final frame of the reflectance-change example are the same as the reflectance and illuminant for the first frame in the illuminant-change example. Pairs of rows show images for the lowest and highest specularities (0.00 and 0.10, respectively) for the Sphere, Gradient, and Scrambled conditions of Experiment 1 and the Bumpy and Marbled conditions of Experiment 2. Note that the color changes in the zero specularity condition are identical for reflectance and illuminant changes, despite the difference in the source of this change. Color reproduction in this figure will not be accurate.
Fig. 5.
Fig. 5. Top panel: chromaticities of the brightest points in the first and final frames of our stimulus animations in the MacLeod and Boynton [17] chromaticity diagram. Yellow + symbols represent surfaces under sunlight, and blue + symbols represent surfaces under skylight. Symbols with less saturated yellow or blue colors indicate chromaticities from stimuli with higher specularity. Each of the black polygons encloses chromaticities from stimuli with a particular specularity. The outermost polygon contains surfaces with zero specularity and the smaller polygons enclose stimuli with higher specularities. The chromaticities of the illuminants themselves are indicated by the green symbols in the centers of the corresponding clusters. Lower four panels: chromaticities visited by the brightest points in our stimulus animations with zero specularity (upper small panels), and specularity = 0.1 (lower small panels) in the same color space as the top panel. Each line connects the chromaticity from the first frame to that from the final frame in one animation. Purple lines (left panels) represent reflectance changes, and orange lines (right panels) represent illuminant changes.
Fig. 6.
Fig. 6. Pseudocolor images to represent the chromatic gradients available in the stimulus images in different conditions of Experiments 1 and 2. The color map represents the chromaticity of the corresponding pixel in the stimulus image, expressed as a proportion of the distance from the chromaticity of the diffuse component ( I R ) to the chromaticity of the illuminant ( I ). Green corresponds to I R and purple to I . By removing the intensity variations that are present in the real stimulus images, these plots emphasize the spatial distribution of chromatic statistics.
Fig. 7.
Fig. 7. Results from real and simulated observers in Experiment 1. The top panels show d at each measured value of specularity and the lower panels show the corresponding ln ( β ) values for the three conditions of Sphere, Gradient and Scrambled. Each real observer is represented by a different colored line (consistent across all plots), as indicated in the key. Error bars show 95% confidence intervals based on the binomial distribution. Each real observer’s data points are slightly horizontally offset by a different amount so that error bars can be seen, although the specularities used were the same for each observer. The black dashed lines represent the simulated observers A, B, and C (see text). The upper solid black line indicates the maximum measurable d , given the number of trials in the experiment.
Fig. 8.
Fig. 8. Results from real and simulated observers in Experiment 2 for the two conditions of Bumpy and Marbled. The formatting of these plots is the same as in Figure 7, and the symbol colors correspond to the same observers. The additional gray lines in the right panel represent the simulated observers A and B using the alternative strategy as described in the text (Sections 2.F and 3.C).

Metrics