Abstract

The present study examines whether increment–decrement asymmetries reported in a number of recent center–surround situations occur in more complex images as well. Subjects saw the CRT simulation of a whole uniformly illuminated array of foreground surfaces presented against a large background surface and, for a number of different viewing contexts, made achromatic settings over a wide range of luminance values. Three results emerged. First, subjects’ achromatic loci did not fall on a single straight line in color space but rather fell on two separate lines intersecting at some point in this space. Second, the intersection points were not identical to but dependent largely on background color and showed only small effects of foreground colors. Third, cone signals that were decremental relative to the intersection point were more responsive to illuminant changes than cone signals that were incremental, the latter additionally showing some variation with foreground colors. The results are interpreted in terms of increment–decrement asymmetries. They suggest that these asymmetries occur in more complex images as well.

© 2001 Optical Society of America

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References

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  1. D. H. Brainard, B. A. Wandell, “Asymmetric color-matching: how color appearance depends on the illuminant,” J. Opt. Soc. Am. A 9, 1433–1448 (1992).
    [CrossRef] [PubMed]
  2. K.-H. Bäuml, “Color appearance: effects of illuminant changes under different surface collections,” J. Opt. Soc. Am. A 11, 531–543 (1994).
    [CrossRef]
  3. M. P. Lucassen, J. Walraven, “Color constancy under natural and artificial illumination,” Vision Res. 36, 2699–2711 (1996).
    [CrossRef] [PubMed]
  4. M. E. Gorzynski, “Achromatic perception in color image displays,” M. S. thesis (Rochester Institute of Technology, Rochester, New York, 1992).
  5. D. H. Brainard, “Color constancy in the nearly natural image. 2. Achromatic loci,” J. Opt. Soc. Am. A 15, 307–325 (1998).
    [CrossRef]
  6. K.-H. Bäuml, “Color constancy: the role of image surfaces in illuminant adjustment,” J. Opt. Soc. Am. A 16, 1521–1530 (1999).
    [CrossRef]
  7. P. K. Kaiser, R. M. Boynton, Human Color Vision, 2nd ed. (Optical Society of AmericaWashington, D.C., 1996).
  8. K.-H. Bäuml, “Illuminant changes under different surface collections: examining some principles of color appearance,” J. Opt. Soc. Am. A 12, 261–271 (1995).
    [CrossRef]
  9. J. Walraven, “Colour signals from incremental and decremental light stimuli,” Vision Res. 17, 71–76 (1977).
    [CrossRef] [PubMed]
  10. J. Krauskopf, “Discrimination and detection of changes in luminance,” Vision Res. 20, 671–677 (1980).
    [CrossRef] [PubMed]
  11. T. W. White, G. E. Irvin, M. C. Williams, “Asymmetry in the brightness and darkness Broca–Sulzer effects,” Vision Res. 20, 723–726 (1980).
    [CrossRef]
  12. R. Mausfeld, R. Niederee, “An inquiry into the relational concepts of colour, based on incremental principles of colour coding for minimal relational stimuli,” Perception 22, 427–462 (1993).
    [CrossRef]
  13. E. J. Chichilnisky, B. A. Wandell, “Seeing gray through the ON and OFF pathways,” Visual Neurosci. 13, 591–596 (1996).
    [CrossRef]
  14. E. J. Chichilnisky, B. A. Wandell, “Trichromatic opponent color classification,” Vision Res. 39, 3444–3458 (1999).
    [CrossRef]
  15. P. Whittle, “Increments and decrements: luminance discrimination,” Vision Res.26, 1677–1691 (1986).
    [CrossRef] [PubMed]
  16. P. Whittle, “Contrast brightness and ordinary seeing,” in Lightness, Brightness, and Transparency, A. L. Gilchrist, ed. (Erlbaum, Hillsdale, N. J., 1994), pp. 111–157.
  17. J. von Kries, “Die Gesichtsempfindungen,” in Handbuch der Physiologie des Menschen, W. Nagel, ed. (Vieweg, Braunschweig, Germany, 1905), Vol. 3, pp. 109–279.
  18. P. B. Delahunt, D. H. Brainard, “Control of chromatic adaptation: signals from separate cone classes interact,” Vision Res. 40, 2885–2903 (2000).
    [CrossRef] [PubMed]
  19. D. B. Judd, “Hue, saturation, and lightness of surface colors with chromatic illumination,” J. Opt. Soc. Am. 30, 2–32 (1940).
    [CrossRef]
  20. H. Helson, “Fundamental problems in color vision. I. The principle governing changes in hue, saturation and lightness of non-selective samples in chromatic illumination,” J. Exp. Psychol. 23, 439–476 (1938).
    [CrossRef]
  21. G. Wyszecki, W. S. Stiles, Color Science, 2nd ed. (Wiley, New York, 1982).
  22. V. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 700 nm,” Vision Res. 15, 161–171 (1975).
    [CrossRef] [PubMed]
  23. When using the CIELUV metric21one has to define a nominally white light for a given context. For this white light I used the color coordinates of the respective illuminated background surface. Additionally, I repeated the analyses using other definitions of the nominally white light. Although the absolute error values varied with the choice of the nominally white light, the pattern of results remained the same. The pattern of results did not even change when the analyses were run in cone space.
  24. For the computation of the cone ratios, incremental and decremental cone signals were coded as differences relative to the level estimate. The incremental cone signals thus were assigned positive coordinates, and the decremental ones were assigned negative coordinates.
  25. Both the experimental illuminants and the experimental surfaces were described by three-dimensional linear models. On the basis of this type of modeling, for each illuminant ∊ a so-called light transformation matrix, Δ∊, can be defined. This 3×3matrix provides a mapping from each 3×1 column vector ρ, which represents a surface, to the cone absorptions that result from this surface when rendered under illuminant ∊. I computed the light transformation matrix for each of the three experimental illuminants and used these matrices to compute perfectly color constant settings (see Wandell,26 pp. 306–308).
  26. B. A. Wandell, Foundations of Vision (Sinauer, Sunderland, Mass., 1995).
  27. L. Arend, A. Reeves, J. Schirillo, R. Goldstein, “Simultaneous color constancy: patterns with diverse Munsell values,” J. Opt. Soc. Am. A 8, 661–672 (1991).
    [CrossRef] [PubMed]
  28. L. Arend, B. Spehar, “Lightness, brightness, and brightness contrast: 1. Illuminance variation,” Percept. Psychophys. 54, 446–456 (1993).
    [CrossRef] [PubMed]
  29. J. W. Jenness, S. K. Shevell, “Color appearance with sparse chromatic context,” Vision Res. 35, 797–805 (1995).
    [CrossRef] [PubMed]
  30. R. O. Brown, D. I. A. MacLeod, “Color appearance depends on the variance of surround colors,” Curr. Biol. 7, 844–849 (1997).
    [CrossRef]
  31. J. A. Schirillo, “Surround articulation. I. brightness judgments,” J. Opt. Soc. Am. A 16, 793–803 (1999).
    [CrossRef]
  32. D. L. Dannemiller, “Computational approaches to color constancy: adaptive and ontogenetic considerations,” Psychol. Rev. 96, 255–266 (1989).
    [CrossRef] [PubMed]
  33. E. H. Land, J. J. McCann, “Lightness and retinex theory,” J. Opt. Soc. Am. 61, 1–11 (1971).
    [CrossRef] [PubMed]
  34. In Experiment 1 the surfaces of collection CN were in more than 80% of the cases pure decrements relative to the darker background BLand in all cases pure decrements relative to the brighter background BH.In Experiment 2 the surfaces of the single-surface collections were in more than 90% of the cases pure decrements relative to background surface BM.In many of the cases in which the foreground surfaces were not pure decrements, they were increments only in one or two of the three cone signals. Also, whenever the cone signals were incremental relative to background their coordinates were only moderately larger than the coordinates of the background field.
  35. D. H. Brainard, W. A. Brunt, J. M. Speigle, “Color constancy in the nearly natural image. 1. Asymmetric matches,” J. Opt. Soc. Am. A 14, 2091–2110 (1997).
    [CrossRef]
  36. L. Arend, A. Reeves, “Simultaneous color constancy,” J. Opt. Soc. Am. A 3, 1743–1751 (1986).
    [CrossRef] [PubMed]
  37. K.-H. Bäuml, “Simultaneous color constancy: how surface color perception varies with the illuminant,” Vision Res. 39, 1531–1550 (1999).
    [CrossRef] [PubMed]
  38. J. A. Schirillo, “Surround articulation. II. Brightness judgments,” J. Opt. Soc. Am. A 16, 804–811 (1999).
    [CrossRef]

2000

P. B. Delahunt, D. H. Brainard, “Control of chromatic adaptation: signals from separate cone classes interact,” Vision Res. 40, 2885–2903 (2000).
[CrossRef] [PubMed]

1999

1998

1997

D. H. Brainard, W. A. Brunt, J. M. Speigle, “Color constancy in the nearly natural image. 1. Asymmetric matches,” J. Opt. Soc. Am. A 14, 2091–2110 (1997).
[CrossRef]

R. O. Brown, D. I. A. MacLeod, “Color appearance depends on the variance of surround colors,” Curr. Biol. 7, 844–849 (1997).
[CrossRef]

1996

E. J. Chichilnisky, B. A. Wandell, “Seeing gray through the ON and OFF pathways,” Visual Neurosci. 13, 591–596 (1996).
[CrossRef]

M. P. Lucassen, J. Walraven, “Color constancy under natural and artificial illumination,” Vision Res. 36, 2699–2711 (1996).
[CrossRef] [PubMed]

1995

1994

1993

R. Mausfeld, R. Niederee, “An inquiry into the relational concepts of colour, based on incremental principles of colour coding for minimal relational stimuli,” Perception 22, 427–462 (1993).
[CrossRef]

L. Arend, B. Spehar, “Lightness, brightness, and brightness contrast: 1. Illuminance variation,” Percept. Psychophys. 54, 446–456 (1993).
[CrossRef] [PubMed]

1992

1991

1989

D. L. Dannemiller, “Computational approaches to color constancy: adaptive and ontogenetic considerations,” Psychol. Rev. 96, 255–266 (1989).
[CrossRef] [PubMed]

1986

1980

J. Krauskopf, “Discrimination and detection of changes in luminance,” Vision Res. 20, 671–677 (1980).
[CrossRef] [PubMed]

T. W. White, G. E. Irvin, M. C. Williams, “Asymmetry in the brightness and darkness Broca–Sulzer effects,” Vision Res. 20, 723–726 (1980).
[CrossRef]

1977

J. Walraven, “Colour signals from incremental and decremental light stimuli,” Vision Res. 17, 71–76 (1977).
[CrossRef] [PubMed]

1975

V. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 700 nm,” Vision Res. 15, 161–171 (1975).
[CrossRef] [PubMed]

1971

1940

1938

H. Helson, “Fundamental problems in color vision. I. The principle governing changes in hue, saturation and lightness of non-selective samples in chromatic illumination,” J. Exp. Psychol. 23, 439–476 (1938).
[CrossRef]

Arend, L.

Bäuml, K.-H.

Boynton, R. M.

P. K. Kaiser, R. M. Boynton, Human Color Vision, 2nd ed. (Optical Society of AmericaWashington, D.C., 1996).

Brainard, D. H.

Brown, R. O.

R. O. Brown, D. I. A. MacLeod, “Color appearance depends on the variance of surround colors,” Curr. Biol. 7, 844–849 (1997).
[CrossRef]

Brunt, W. A.

Chichilnisky, E. J.

E. J. Chichilnisky, B. A. Wandell, “Trichromatic opponent color classification,” Vision Res. 39, 3444–3458 (1999).
[CrossRef]

E. J. Chichilnisky, B. A. Wandell, “Seeing gray through the ON and OFF pathways,” Visual Neurosci. 13, 591–596 (1996).
[CrossRef]

Dannemiller, D. L.

D. L. Dannemiller, “Computational approaches to color constancy: adaptive and ontogenetic considerations,” Psychol. Rev. 96, 255–266 (1989).
[CrossRef] [PubMed]

Delahunt, P. B.

P. B. Delahunt, D. H. Brainard, “Control of chromatic adaptation: signals from separate cone classes interact,” Vision Res. 40, 2885–2903 (2000).
[CrossRef] [PubMed]

Goldstein, R.

Gorzynski, M. E.

M. E. Gorzynski, “Achromatic perception in color image displays,” M. S. thesis (Rochester Institute of Technology, Rochester, New York, 1992).

Helson, H.

H. Helson, “Fundamental problems in color vision. I. The principle governing changes in hue, saturation and lightness of non-selective samples in chromatic illumination,” J. Exp. Psychol. 23, 439–476 (1938).
[CrossRef]

Irvin, G. E.

T. W. White, G. E. Irvin, M. C. Williams, “Asymmetry in the brightness and darkness Broca–Sulzer effects,” Vision Res. 20, 723–726 (1980).
[CrossRef]

Jenness, J. W.

J. W. Jenness, S. K. Shevell, “Color appearance with sparse chromatic context,” Vision Res. 35, 797–805 (1995).
[CrossRef] [PubMed]

Judd, D. B.

Kaiser, P. K.

P. K. Kaiser, R. M. Boynton, Human Color Vision, 2nd ed. (Optical Society of AmericaWashington, D.C., 1996).

Krauskopf, J.

J. Krauskopf, “Discrimination and detection of changes in luminance,” Vision Res. 20, 671–677 (1980).
[CrossRef] [PubMed]

Land, E. H.

Lucassen, M. P.

M. P. Lucassen, J. Walraven, “Color constancy under natural and artificial illumination,” Vision Res. 36, 2699–2711 (1996).
[CrossRef] [PubMed]

MacLeod, D. I. A.

R. O. Brown, D. I. A. MacLeod, “Color appearance depends on the variance of surround colors,” Curr. Biol. 7, 844–849 (1997).
[CrossRef]

Mausfeld, R.

R. Mausfeld, R. Niederee, “An inquiry into the relational concepts of colour, based on incremental principles of colour coding for minimal relational stimuli,” Perception 22, 427–462 (1993).
[CrossRef]

McCann, J. J.

Niederee, R.

R. Mausfeld, R. Niederee, “An inquiry into the relational concepts of colour, based on incremental principles of colour coding for minimal relational stimuli,” Perception 22, 427–462 (1993).
[CrossRef]

Pokorny, J.

V. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 700 nm,” Vision Res. 15, 161–171 (1975).
[CrossRef] [PubMed]

Reeves, A.

Schirillo, J.

Schirillo, J. A.

Shevell, S. K.

J. W. Jenness, S. K. Shevell, “Color appearance with sparse chromatic context,” Vision Res. 35, 797–805 (1995).
[CrossRef] [PubMed]

Smith, V.

V. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 700 nm,” Vision Res. 15, 161–171 (1975).
[CrossRef] [PubMed]

Spehar, B.

L. Arend, B. Spehar, “Lightness, brightness, and brightness contrast: 1. Illuminance variation,” Percept. Psychophys. 54, 446–456 (1993).
[CrossRef] [PubMed]

Speigle, J. M.

Stiles, W. S.

G. Wyszecki, W. S. Stiles, Color Science, 2nd ed. (Wiley, New York, 1982).

von Kries, J.

J. von Kries, “Die Gesichtsempfindungen,” in Handbuch der Physiologie des Menschen, W. Nagel, ed. (Vieweg, Braunschweig, Germany, 1905), Vol. 3, pp. 109–279.

Walraven, J.

M. P. Lucassen, J. Walraven, “Color constancy under natural and artificial illumination,” Vision Res. 36, 2699–2711 (1996).
[CrossRef] [PubMed]

J. Walraven, “Colour signals from incremental and decremental light stimuli,” Vision Res. 17, 71–76 (1977).
[CrossRef] [PubMed]

Wandell, B. A.

E. J. Chichilnisky, B. A. Wandell, “Trichromatic opponent color classification,” Vision Res. 39, 3444–3458 (1999).
[CrossRef]

E. J. Chichilnisky, B. A. Wandell, “Seeing gray through the ON and OFF pathways,” Visual Neurosci. 13, 591–596 (1996).
[CrossRef]

D. H. Brainard, B. A. Wandell, “Asymmetric color-matching: how color appearance depends on the illuminant,” J. Opt. Soc. Am. A 9, 1433–1448 (1992).
[CrossRef] [PubMed]

B. A. Wandell, Foundations of Vision (Sinauer, Sunderland, Mass., 1995).

White, T. W.

T. W. White, G. E. Irvin, M. C. Williams, “Asymmetry in the brightness and darkness Broca–Sulzer effects,” Vision Res. 20, 723–726 (1980).
[CrossRef]

Whittle, P.

P. Whittle, “Increments and decrements: luminance discrimination,” Vision Res.26, 1677–1691 (1986).
[CrossRef] [PubMed]

P. Whittle, “Contrast brightness and ordinary seeing,” in Lightness, Brightness, and Transparency, A. L. Gilchrist, ed. (Erlbaum, Hillsdale, N. J., 1994), pp. 111–157.

Williams, M. C.

T. W. White, G. E. Irvin, M. C. Williams, “Asymmetry in the brightness and darkness Broca–Sulzer effects,” Vision Res. 20, 723–726 (1980).
[CrossRef]

Wyszecki, G.

G. Wyszecki, W. S. Stiles, Color Science, 2nd ed. (Wiley, New York, 1982).

Curr. Biol.

R. O. Brown, D. I. A. MacLeod, “Color appearance depends on the variance of surround colors,” Curr. Biol. 7, 844–849 (1997).
[CrossRef]

J. Exp. Psychol.

H. Helson, “Fundamental problems in color vision. I. The principle governing changes in hue, saturation and lightness of non-selective samples in chromatic illumination,” J. Exp. Psychol. 23, 439–476 (1938).
[CrossRef]

J. Opt. Soc. Am.

J. Opt. Soc. Am. A

K.-H. Bäuml, “Color appearance: effects of illuminant changes under different surface collections,” J. Opt. Soc. Am. A 11, 531–543 (1994).
[CrossRef]

J. A. Schirillo, “Surround articulation. I. brightness judgments,” J. Opt. Soc. Am. A 16, 793–803 (1999).
[CrossRef]

J. A. Schirillo, “Surround articulation. II. Brightness judgments,” J. Opt. Soc. Am. A 16, 804–811 (1999).
[CrossRef]

K.-H. Bäuml, “Color constancy: the role of image surfaces in illuminant adjustment,” J. Opt. Soc. Am. A 16, 1521–1530 (1999).
[CrossRef]

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

D. H. Brainard, W. A. Brunt, J. M. Speigle, “Color constancy in the nearly natural image. 1. Asymmetric matches,” J. Opt. Soc. Am. A 14, 2091–2110 (1997).
[CrossRef]

L. Arend, A. Reeves, “Simultaneous color constancy,” J. Opt. Soc. Am. A 3, 1743–1751 (1986).
[CrossRef] [PubMed]

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

D. H. Brainard, B. A. Wandell, “Asymmetric color-matching: how color appearance depends on the illuminant,” J. Opt. Soc. Am. A 9, 1433–1448 (1992).
[CrossRef] [PubMed]

K.-H. Bäuml, “Illuminant changes under different surface collections: examining some principles of color appearance,” J. Opt. Soc. Am. A 12, 261–271 (1995).
[CrossRef]

Percept. Psychophys.

L. Arend, B. Spehar, “Lightness, brightness, and brightness contrast: 1. Illuminance variation,” Percept. Psychophys. 54, 446–456 (1993).
[CrossRef] [PubMed]

Perception

R. Mausfeld, R. Niederee, “An inquiry into the relational concepts of colour, based on incremental principles of colour coding for minimal relational stimuli,” Perception 22, 427–462 (1993).
[CrossRef]

Psychol. Rev.

D. L. Dannemiller, “Computational approaches to color constancy: adaptive and ontogenetic considerations,” Psychol. Rev. 96, 255–266 (1989).
[CrossRef] [PubMed]

Vision Res.

P. B. Delahunt, D. H. Brainard, “Control of chromatic adaptation: signals from separate cone classes interact,” Vision Res. 40, 2885–2903 (2000).
[CrossRef] [PubMed]

K.-H. Bäuml, “Simultaneous color constancy: how surface color perception varies with the illuminant,” Vision Res. 39, 1531–1550 (1999).
[CrossRef] [PubMed]

J. W. Jenness, S. K. Shevell, “Color appearance with sparse chromatic context,” Vision Res. 35, 797–805 (1995).
[CrossRef] [PubMed]

J. Walraven, “Colour signals from incremental and decremental light stimuli,” Vision Res. 17, 71–76 (1977).
[CrossRef] [PubMed]

J. Krauskopf, “Discrimination and detection of changes in luminance,” Vision Res. 20, 671–677 (1980).
[CrossRef] [PubMed]

T. W. White, G. E. Irvin, M. C. Williams, “Asymmetry in the brightness and darkness Broca–Sulzer effects,” Vision Res. 20, 723–726 (1980).
[CrossRef]

E. J. Chichilnisky, B. A. Wandell, “Trichromatic opponent color classification,” Vision Res. 39, 3444–3458 (1999).
[CrossRef]

M. P. Lucassen, J. Walraven, “Color constancy under natural and artificial illumination,” Vision Res. 36, 2699–2711 (1996).
[CrossRef] [PubMed]

V. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 700 nm,” Vision Res. 15, 161–171 (1975).
[CrossRef] [PubMed]

Visual Neurosci.

E. J. Chichilnisky, B. A. Wandell, “Seeing gray through the ON and OFF pathways,” Visual Neurosci. 13, 591–596 (1996).
[CrossRef]

Other

P. Whittle, “Increments and decrements: luminance discrimination,” Vision Res.26, 1677–1691 (1986).
[CrossRef] [PubMed]

P. Whittle, “Contrast brightness and ordinary seeing,” in Lightness, Brightness, and Transparency, A. L. Gilchrist, ed. (Erlbaum, Hillsdale, N. J., 1994), pp. 111–157.

J. von Kries, “Die Gesichtsempfindungen,” in Handbuch der Physiologie des Menschen, W. Nagel, ed. (Vieweg, Braunschweig, Germany, 1905), Vol. 3, pp. 109–279.

When using the CIELUV metric21one has to define a nominally white light for a given context. For this white light I used the color coordinates of the respective illuminated background surface. Additionally, I repeated the analyses using other definitions of the nominally white light. Although the absolute error values varied with the choice of the nominally white light, the pattern of results remained the same. The pattern of results did not even change when the analyses were run in cone space.

For the computation of the cone ratios, incremental and decremental cone signals were coded as differences relative to the level estimate. The incremental cone signals thus were assigned positive coordinates, and the decremental ones were assigned negative coordinates.

Both the experimental illuminants and the experimental surfaces were described by three-dimensional linear models. On the basis of this type of modeling, for each illuminant ∊ a so-called light transformation matrix, Δ∊, can be defined. This 3×3matrix provides a mapping from each 3×1 column vector ρ, which represents a surface, to the cone absorptions that result from this surface when rendered under illuminant ∊. I computed the light transformation matrix for each of the three experimental illuminants and used these matrices to compute perfectly color constant settings (see Wandell,26 pp. 306–308).

B. A. Wandell, Foundations of Vision (Sinauer, Sunderland, Mass., 1995).

M. E. Gorzynski, “Achromatic perception in color image displays,” M. S. thesis (Rochester Institute of Technology, Rochester, New York, 1992).

G. Wyszecki, W. S. Stiles, Color Science, 2nd ed. (Wiley, New York, 1982).

P. K. Kaiser, R. M. Boynton, Human Color Vision, 2nd ed. (Optical Society of AmericaWashington, D.C., 1996).

In Experiment 1 the surfaces of collection CN were in more than 80% of the cases pure decrements relative to the darker background BLand in all cases pure decrements relative to the brighter background BH.In Experiment 2 the surfaces of the single-surface collections were in more than 90% of the cases pure decrements relative to background surface BM.In many of the cases in which the foreground surfaces were not pure decrements, they were increments only in one or two of the three cone signals. Also, whenever the cone signals were incremental relative to background their coordinates were only moderately larger than the coordinates of the background field.

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Figures (8)

Fig. 1
Fig. 1

Visual display. Subjects saw CRT simulations of a collection of 24 flat matte foreground surfaces (rectangular regions) and a test object (circular region), both presented against a large background surface. The array of foreground surfaces and the background surface were rendered under the same spatially uniform illumination. The subjects pressed buttons to adjust the appearance of the test object.

Fig. 2
Fig. 2

Achromatic settings (Experiment 1). (A) Settings of subject TE (collection CN, yellow illuminant, background surface BH). (B) Settings of subject KHB (collection CN, yellow illuminant, background surface BL). L and M (left panels) coordinates and L and S (right panels) coordinates of the single settings are compared. Solid lines represent the predictions of these settings, which are based on the ID model. Dashed lines extend the solid lines to demonstrate that the settings do not fall on a single straight line. (x, coordinates of the illuminated background field; see also Fig. 3 below.)

Fig. 3
Fig. 3

Level estimates (Experiment 1). Chromaticity (A) and luminance (B) coordinates of the level estimates are shown and compared with the respective coordinates of the illuminated background surface (⊗, coordinates of the bright background field; ⊕, coordinates of the dark background field; ○, level coordinates for the bright background condition; ●, level coordinates for the dark background condition; B=blue illumination; N=neutral illumination; Y=yellow illumination).

Fig. 4
Fig. 4

Relating level luminance and background luminance. A power function fit is shown relating the two variables for each of the two subjects (●, data of Experiment 1; ○, data of Experiment 2).

Fig. 5
Fig. 5

Effect of illuminant changes (Experiment 1). L and S coordinates (left panel) and M and S coordinates (right panel) of the achromatic settings of subjects TE and KHB under the blue (○) and the yellow (●) illuminant are shown. The settings are plotted as differences from the estimated neutral points. Solid lines represent the predictions of the settings that are based on the ID model. Dashed lines represent the settings that the subject would have made if he had adjusted perfectly to the illuminant changes. (A) Subject TE (collection CN, background surface BH). (B) Subject KHB (collection CN, background surface BL).

Fig. 6
Fig. 6

Achromatic settings (Experiment 2). L and M coordinates (left panels) and L and S coordinates (right panels) of achromatic settings of subject CK under the yellow illuminant are shown. (A) Settings for surface conditions CU (●) and CG (○). (B) Settings for surface conditions CBM (●) and CB (○). Solid lines represent the predictions of the settings that are based on the ID model. (x, coordinates of the illuminated background field; see also Fig. 7.)

Fig. 7
Fig. 7

Level estimates (Experiment 2). Chromaticity (A) and luminance (B) coordinates of the level estimates are shown and compared to the respective coordinates of the illuminated background surface (⊕, coordinates of the background field; ●, level coordinates for surface collection CB; ○, level coordinates for surface collection CBM; ◁, level coordinates for surface collection CG; ▷, level coordinates for surface collection CGM; x, level coordinates for surface collection CR; +, level coordinates for surface collection CRM;  * , level coordinates for surface collection CU; B=blue illumination; Y=yellow illumination).

Fig. 8
Fig. 8

Achromatic settings (Experiment 2). (A) Settings of subject CK for the yellowish illuminant, (B) settings of subject KHB for the bluish illuminant. L and S coordinates (left panels) and M and S coordinates (right panels) of the settings of all seven surface conditions are shown. Solid lines represent the predictions of these settings, which are based on a variant of the ID model, in which it is assumed that image surfaces do not affect the settings (see text). Dashed lines extend the solid lines to demonstrate that the settings do not fall on a single straight line. (x, coordinates of the illuminated background field; see also Fig. 7.)

Tables (2)

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Table 1 Scale Factors Used to Compute the Incremental M/L, S/L, and S/M Cone Ratios from the Respective Decremental Cone Ratios in Experiment 1a

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Table 2 Scale Factors Used to Compute the Incremental M/L, S/L, and S/M Cone Ratios from the Respective Decremental Cone Ratios in Experiment a

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