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Color scaling of discs and natural objects at different luminance levels

Published online by Cambridge University Press:  06 September 2006

THORSTEN HANSEN
Affiliation:
University of Giessen, Department of Psychology, Giessen, Germany
KARL R. GEGENFURTNER
Affiliation:
University of Giessen, Department of Psychology, Giessen, Germany

Abstract

Assigning a basic color name to an object and rating the amount of a particular hue is a fundamental visual capability. Traditional color scaling studies have used increment flashes or isoluminant stimuli of a homogeneous color. Natural objects, however, do not contain a single color but are characterized by a distribution of different chromatic hues. Here we study color scaling using photographs of natural fruit objects. Stimuli were either homogeneous spots, digital photographs of fruit objects (e.g., banana), or outline shapes of the fruit objects. Stimuli were displayed on a CRT monitor on a homogeneous white background; its luminance was varied above and below the medium gray. The chromaticity of the stimuli was varied in 36 equally spaced chromatic directions in the isoluminant plane of the Derrington-Krauskopf-Lennie (DKL) color space. For each stimuli, subjects rated the amount of red, green, blue, and yellow in the stimulus on a scale from 0–8. In agreement with earlier studies we found that the positions of the peak ratings for each color do not coincide with the cardinal axis of DKL color space and are largely invariant under changes of the background luminance. For the average rating we found a dependence on background luminance for all colors: yellow ratings increase with darker backgrounds, whereas ratings for the other colors, in particular green, decrease. For the fruit objects, we found a selective increase in the average color rating for the natural fruit color. For example, the average rating for yellow was 1.7 times higher for the banana images compared to disc stimuli. No such selective increase was found for outline shapes. We conclude that the distribution of hues in natural objects with a characteristic object color can have a profound effect on color scaling and color appearance.

Type
PERCEPTION
Copyright
© 2006 Cambridge University Press

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References

REFERENCES

Brainard, D.H. (1996). Cone contrast and opponent modulation color spaces. In Human Color Vision, eds. Kaiser, P. & Boynton, R.M., pp. 563579. Washington, DC: Optical Society of America.
De Valois, R.L., Abramov, I., & Jacobs, G.H. (1966). Analysis of response patterns of LGN cells. Journal of the Optical Society of America 56, 966977.CrossRefGoogle Scholar
De Valois, R.L., De Valois, K.K., & Mahon, L.E. (2000). Contribution of S opponent cells to color appearance. Proceedings of the National Academy of Sciences 97, 512517.CrossRefGoogle Scholar
De Valois, R.L., De Valois, K.K., Switkes, E., & Mahon, L. (1997). Hue scaling of isoluminant and cone-specific lights. Vision Research 37, 885897.CrossRefGoogle Scholar
Derrington, A.M., Krauskopf, J., & Lennie, P. (1984). Chromatic mechanisms in lateral geniculate nucleus of macaque. The Journal of Physiology 357, 241265.CrossRefGoogle Scholar
Gegenfurtner, K.R. (2003). Cortical mechanisms of colour vision. Nature Reviews Neuroscience 4, 563572.CrossRefGoogle Scholar
Gegenfurtner, K.R. & Walter, S. (2004). The contribution of memory colours to colour constancy. Perception (Suppl.) 33, 40.Google Scholar
Hering, E. (1964). Grundzüge der Lehre vom Lichtsinn. English Translation “Outlines of a Theory of the Light Sense,” eds. Hurvich, L.M. & Jameson, D. Cambridge: Harvard University Press.
Hurvich, L.M. & Jameson, D. (1955). Some quantitative aspects of an opponent-colors theory. II. Brightness, saturation, and hue in normal and dichromatic vision. Journal of the Optical Society of America 45, 602616.Google Scholar
Irtel, H. (1992). Computing data for color-vision modeling. Behavior Research Methods, Instruments, & Computers 24, 397401.CrossRefGoogle Scholar
Judd, D.B. (1951). Report of US. Secretariat committee on colorimetry and artificial daylight. In Proceedings of the Twelfth Session of the CIE, p. 11. Paris, Stockholm: Bureau Central de la CIE.
Krauskopf, J., Williams, D.R., & Heeley, D.W. (1982). Cardinal directions of color space. Vision Research 22, 11231131.CrossRefGoogle Scholar
Larimer, J. (1974). Opponent-process additivity–I: red-green equilibria. Vision Research 14, 11271140.CrossRefGoogle Scholar
Larimer, J., Krantz, D.H., & Cicerone, C.M. (1975). Opponent process additivity. II. Yellow/blue equilibria and nonlinear models. Vision Research 15, 723731.Google Scholar
MacLeod, D.I. & Boynton, R.M. (1979). Chromaticity diagram showing cone excitation by stimuli of equal luminance. Journal of the Optical Society of America 69, 11831186.CrossRefGoogle Scholar
Malkoc, G., Kay, P., & Webster, M.A. (2005). Variations in normal color vision. IV. Binary hues and hue scaling. Journal of the Optical Society of America (A) 22, 21542168.CrossRefGoogle Scholar
Schrödinger, E. (1995). Über das Verhältnis der Vierfarben- zur Dreifarbentheorie. Sitzungsberichte der Akademie der Wissenschaften in Wien. Mathematisch-naturwissenschaftliche Klasse, Abteilung 2a, 134, 471–490. 1925. Reprinted in Farbe 41, 178197.Google Scholar
Smith, V.C. & Pokorny, J. (1975). Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm. Vision Research 15, 161171.CrossRefGoogle Scholar
Valberg, A. (2001). Unique hues: an old problem for a new generation. Vision Research 41, 16451657.CrossRefGoogle Scholar
Webster, M.A., Miyahara, E., Malkoc, G., & Raker, V.E. (2000). Variations in normal color vision. II. Unique hues. Journal of the Optical Society of America (A) 17, 15451555.CrossRefGoogle Scholar
Wuerger, S.M., Atkinson, P., & Cropper, S. (2005). The cone inputs to the unique-hue mechanisms. Vision Research 45, 32103223.CrossRefGoogle Scholar
Wyszecki, G. & Stiles, W.S. (1982). Color Science. Concepts and Methods, Quantitative Data and Formulae, 2nd edition. New York: Wiley.