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Color constancy in natural scenes with and without an explicit illuminant cue

Published online by Cambridge University Press:  06 September 2006

KINJIRO AMANO
Affiliation:
Sensing, Imaging, and Signal Processing Group, School of Electrical and Electronic Engineering, University of Manchester, Manchester, United Kingdom
DAVID H. FOSTER
Affiliation:
Sensing, Imaging, and Signal Processing Group, School of Electrical and Electronic Engineering, University of Manchester, Manchester, United Kingdom
SÉRGIO M.C. NASCIMENTO
Affiliation:
Department of Physics, Gualtar Campus, University of Minho, Braga, Portugal

Abstract

Observers can generally make reliable judgments of surface color in natural scenes despite changes in an illuminant that is out of view. This ability has sometimes been attributed to observers' estimating the spectral properties of the illuminant in order to compensate for its effects. To test this hypothesis, two surface-color-matching experiments were performed with images of natural scenes obtained from high-resolution hyperspectral images. In the first experiment, the sky illuminating the scene was directly visible to the observer, and its color was manipulated. In the second experiment, a large gray sphere was introduced into the scene so that its illumination by the sun and sky was also directly visible to the observer, and the color of that illumination was manipulated. Although the degree of color constancy varied across this and other variations of the images, there was no reliable effect of illuminant color. Even when the sky was eliminated from view, color constancy did not worsen. Judging surface color in natural scenes seems to be independent of an explicit illuminant cue.

Type
SURFACE COLOR PERCEPTION
Copyright
© 2006 Cambridge University Press

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References

REFERENCES

Amano, K. & Foster, D.H. (2004). Colour constancy under simultaneous changes in surface position and illuminant. Proceedings of the Royal Society of London Series B 271, 23192326.Google Scholar
Amano, K., Foster, D.H., & Nascimento, S.M. (2005). Minimalist surface-colour matching. Perception 34, 10091013.Google Scholar
Arend, L. & Reeves, A. (1986). Simultaneous color constancy. Journal of the Optical Society of America A. Optics, Image Science, and Vision 3, 17431751.Google Scholar
Arend, L.E., Jr., Reeves, A., Schirillo, J., & Goldstein, R. (1991). Simultaneous color constancy: Papers with diverse Munsell values. Journal of the Optical Society of America A. Optics, Image Science, and Vision 8, 661672.Google Scholar
Bramwell, D.I. & Hurlbert, A.C. (1996). Measurements of colour constancy by using a forced-choice matching technique. Perception 25, 229241.Google Scholar
Buchsbaum, G. (1980). A spatial processor model for object colour perception. Journal of the Franklin Institute 310, 126.Google Scholar
Cleveland, W.S. & Devlin, S.J. (1988). Locally weighted regression: An approach to regression analysis by local fitting. Journal of the American Statistical Association 83, 596610.Google Scholar
Craven, B.J. & Foster, D.H. (1992). An operational approach to colour constancy. Vision Research 32, 13591366.Google Scholar
de Almeida, V.M.N., Fiadeiro, P.T., & Nascimento, S.M.C. (2004). Color constancy by asymmetric color matching with real objects in three-dimensional scenes. Visual Neuroscience 21, 341345.Google Scholar
D'Zmura, M. & Iverson, G. (1993a). Color constancy. I. Basic theory of two-stage linear recovery of spectral descriptions for lights and surfaces. Journal of the Optical Society of America A. Optics, Image Science, and Vision 10, 21482165.Google Scholar
D'Zmura, M. & Iverson, G. (1993b). Color constancy. II. Results for two-stage linear recovery of spectral descriptions for lights and surfaces. Journal of the Optical Society of America A. Optics, Image Science, and Vision 10, 21662180.Google Scholar
D'Zmura, M. & Iverson, G. (1994). Color constancy. III. General linear recovery of spectral descriptions for lights and surfaces. Journal of the Optical Society of America A. Optics, Image Science, and Vision 11, 23892400.Google Scholar
Efron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. New York: Chapman and Hall.
Finlayson, G.D., Hordley, S.D., & Hubel, P.M. (2001). Color by correlation: A simple, unifying framework for color constancy. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 12091221.Google Scholar
Foster, D.H. (2003). Does colour constancy exist? Trends in Cognitive Sciences 7, 439443.Google Scholar
Foster, D.H., Amano, K., & Nascimento, S.M. (2006a). Color constancy in natural scenes explained by global image statistics. Visual Neuroscience, 23, 341349.Google Scholar
Foster, D.H., Amano, K., & Nascimento, S.M.C. (2001a). Colour constancy from temporal cues: Better matches with less variability under fast illuminant changes. Vision Research 41, 285293.Google Scholar
Foster, D.H., Amano, K., Nascimento, S.M.C., & Foster, M.J. (2006b). Frequency of metamerism in natural scenes. Journal of the Optical Society of America A. Optics, Image Science, and Vision (in press).Google Scholar
Foster, D.H. & Nascimento, S.M.C. (1994). Relational colour constancy from invariant cone-excitation ratios. Proceedings of the Royal Society of London Series B 257, 115121.Google Scholar
Foster, D.H., Nascimento, S.M.C., & Amano, K. (2004). Information limits on neural identification of colored surfaces in natural scenes. Visual Neuroscience 21, 331336.Google Scholar
Foster, D.H., Nascimento, S.M.C., Amano, K., Arend, L., Linnell, K.J., Nieves, J.L., Plet, S., & Foster, J.S. (2001b). Parallel detection of violations of color constancy. Proceedings of the National Academy of Sciences of the U.S.A. 98, 81518156.Google Scholar
Golz, J. & MacLeod, D.I.A. (2002). Influence of scene statistics on colour constancy. Nature 415, 637640.Google Scholar
Judd, D.B., MacAdam, D.L., & Wyszecki, G. (1964). Spectral distribution of typical daylight as a function of correlated color temperature. Journal of the Optical Society of America 54, 10311040.Google Scholar
Kraft, J.M. & Brainard, D.H. (1999). Mechanisms of color constancy under nearly natural viewing. Proceedings of the National Academy of Sciences of the U.S.A. 96, 307312.Google Scholar
Land, E.H. & McCann, J.J. (1971). Lightness and retinex theory. Journal of the Optical Society of America 61, 111.Google Scholar
Linnell, K.J. & Foster, D.H. (1997). Space-average scene colour used to extract illuminant information. In John Dalton's Colour Vision Legacy, eds. Dickinson, C., Murray, I. & Carden, D., pp. 501509. London: Taylor and Francis.
Linnell, K.J. & Foster, D.H. (2002). Scene articulation: Dependence of illuminant estimates on number of surfaces. Perception 31, 151159.Google Scholar
Maloney, L.T. (1999). Physics-based approaches to modeling surface color perception. In Color Vision: From Genes to Perception, eds. Gegenfurtner, K.R. & Sharpe, L.T., pp. 387416. Cambridge: Cambridge University Press.
Nascimento, S.M.C., Ferreira, F.P., & Foster, D.H. (2002). Statistics of spatial cone-excitation ratios in natural scenes. Journal of the Optical Society of America A 19, 14841490.Google Scholar
Smithson, H.E. (2005). Sensory, computational and cognitive components of human colour constancy. Philosophical Transactions of the Royal Society B 360, 13291346.Google Scholar
von Helmholtz, H. (1867). Handbuch der Physiologischen Optik, Vol. 2. Second edition. Leipzig: Leopold Voss. Translated as Helmholtz's Treatise on Physiological Optics, ed. Southall, J.P.C., pp. 286–287. Third edition. Washington, DC: Optical Society of America, 1924. Reprint, New York: Dover Publications, 1962.
Yang, J.N. & Maloney, L.T. (2001). Illuminant cues in surface color perception: Tests of three candidate cues. Vision Research 41, 25812600.Google Scholar