Skip to main content
Log in

A novel algorithm for color constancy

  • Published:
International Journal of Computer Vision Aims and scope Submit manuscript

Abstract

Color constancy is the skill by which it is possible to tell the color of an object even under a colored light. I interpret the color of an object as its color under a fixed canonical light, rather than as a surface reflectance function. This leads to an analysis that shows two distinct sets of circumstances under which color constancy is possible. In this framework, color constancy requires estimating the illuminant under which the image was taken. The estimate is then used to choose one of a set of linear maps, which is applied to the image to yield a color descriptor at each point. This set of maps is computed in advance.

The illuminant can be estimated using image measurements alone, because, given a number of weak assumptions detailed in the text, the color of the illuminant is constrained by the colors observed in the image. This constraint arises from the fact that surfaces can reflect no more light than is cast on them. For example, if one observes a patch that excites the red receptor strongly, the illuminant cannot have been deep blue.

Two algorithms are possible using this constraint, corresponding to different assumptions about the world. The first algorithm, Crule will work for any surface reflectance. Crule corresponds to a form of coefficient rule, but obtains the coefficients by using constraints on illuminant color. The set of illuminants for which Crule will be successful depends strongly on the choice of photoreceptors: for narrowband photoreceptors, Crule will work in an unrestricted world. The second algorithm, Mwext, requires that both surface reflectances and illuminants be chosen from finite dimensional spaces; but under these restrictive conditions it can recover a large number of parameters in the illuminant, and is not an attractive model of human color constancy.

Crule has been tested on real images of Mondriaans, and works well. I show results for Crule and for the Retinex algorithm of Land (Land 1971; Land 1983; Land 1985) operating on a number of real images. The experimental work shows that for good constancy, a color constancy system will need to adjust the gain of the receptors it employs in a fashion analagous to adaptation in humans.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • H.B. Barlow and J.D. Mollon, The Senses. Cambridge University Press: Cambridge, 1982.

    Google Scholar 

  • C.J. Bartleson, “A review of chromatic adaptation.” In F.W. Billmeyer and G. Wyszecki (eds.), Color 77. Adam Hilger: Bristol, 1977.

    Google Scholar 

  • J. Beck, Surface Color Perception, Cornell University Press: Ithaca, NY, 1972.

    Google Scholar 

  • A. Blake, “Boundary conditions for lightness computation in Mondriaan world.” In D. Ottoson and S. Zeki (eds.), Central and Peripheral Mechanisms of Color Vision. Macmillan: New York, 1985.

    Google Scholar 

  • W. Boothby, An Introduction to Differentiable Manifolds and Riemannian Geometry. Academic Press: San Diego, CA, 1986.

    Google Scholar 

  • G. Buchsbaum, “A spatial processor model for object color perception,” J. Franklin Inst. 310: 1–26, 1980.

    Google Scholar 

  • D.H. Brainard and B.A. Wandell, “Analysis of the Retinex theory of color vision,” J. Opt. Soc. Amer. A 3: 1651–1661, 1986.

    Google Scholar 

  • G.J. Brelstaff, “Inferring surface shape from specular reflections,” Ph.D. thesis, University of Edinburgh: Edinburgh, 1988.

  • G. Brelstaff and A. Blake, “Computing lightness,” Pattern Recognition Letters 5: 129–138, 1987.

    Google Scholar 

  • M.H. Brill, “A device performing illuminant-invariant assessment of chromatic relations,” J. Theor. Biol. 71: 473–478, 1978.

    Google Scholar 

  • M.H. Brill, “Computer simulation of object color recognisers,” J. Opt. Soc. Amer. 69: 1405, 1979.

    Google Scholar 

  • M.H. 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.

    Google Scholar 

  • S.A. Cameron, “Efficient intersection tests for objects defined constructively,” Intern. J. Robotics Res. 8: 1, 1989.

    Google Scholar 

  • M. D'Zmura and P. Lennie, “Mechanisms of color constancy,” J. Opt. Soc. Amer. A 3 (10): 1662–1672, 1986.

    Google Scholar 

  • R.K. Eisenschitz, Matrix Algebra for Physicists. Heinemann: London, 1966.

    Google Scholar 

  • D.A. Forsyth, “A novel algorithm for colour constancy,” Proc. 2nd Intern. Conf. Comput. Vision, Tampa, 1988a.

  • D.A. Forsyth, “Colour constancy and its applications in machine vision.” Ph.D. thesis, University of Oxford, Oxford, 1988b.

  • D.A. Forsyth and A. Zisserman, “Mutual illumination,” Proc. 26th IEEE Conf. Comput. Vision and Pattern Recog. Las Vegas, 1989.

  • D.A. Forsyth and A. Zisserman, “Shape from shading in the light of mutual illumination,” Image and Vision Computing, 1990 (in press).

  • B.V. Funt and M. Drew, “Color constancy computation in near-Mondriaan scenes using a finite dimensional linear model,” Proc. IEEE Conf. Comput. Vision and Pattern Recog.1988.

  • R. Gershon, “The use of colour in computational vision.” Ph.D. thesis, University of Toronto, 1988.

  • R. Gershon, A. Jepson, and J. Tsotsos, “Ambient illumination and the determination of material changes,” J. Opt. Soc. Amer. A 3: 1700–1707, 1986.

    Google Scholar 

  • A.L. Gilchrist, S. Delman, and A. Jacobsen, “The classification and integration of edges as critical to the perception of reflectance and illumination,” Perception and Psychophysics 33: 425–436, 1983.

    Google Scholar 

  • J. Ho, B.V. Funt, and M.S. Drew, “Disambiguation of illumination and surface reflectance from spectral power distribution of color signal: Theory and applications,” CSS/LCCR TR 88-18, Centre for Systems Science, Simon Fraser University, 1988.

  • J. Ho, M.S. Drew, and B.V. Funt, “Color constancy from mutual reflection,” CSS/LCCR TR 89-02, Centre for Systems Science, Simon Fraser University, 1989.

  • B.K.P.H. Horn, “Determining lightness from an image,” Comput. Graph. Image Proc. 3: 277–299, 1974.

    Google Scholar 

  • D.B. Judd, “Appraisal of Land's work on two-primary colour projections,” J. Opt. Soc. Amer. 50: 254–268, 1960.

    Google Scholar 

  • S. Kawata, S. Sasaki, and S. Minami, “Component analysis of spatial and spectral patterns in multispectral images. I. Basis,” J. Opt. Soc. Amer. A 4: 2101–2106, 1987.

    Google Scholar 

  • G.J. Klinker, S.A. Shafer, and T. Kanade, “Using a colour reflection model to separate highlights from object colour,” Proc. 1st Intern. Conf. Comput. Vision. London, 1987.

  • J.J. Koenderink, “Color atlas theory,” J. Opt. Soc. Amer. A 4: 1314–1321, 1987.

    Google Scholar 

  • J. von Kries, “Beitrag zur Physiologic der Gesichtsempfindung,” Arch. Anat. Physiol. 2: 505–524, 1878.

    Google Scholar 

  • E.H. Land, “Color vision and the natural image, Part I,” Proc. Natl. Acad. Sci. U.S.A. 45: 115–129, 1959a.

    Google Scholar 

  • E.H. Land, “Color vision and the natural image. Part II,” Proc. Natl. Acad. Sci. U.S.A. 45: 636–644, 1959b.

    Google Scholar 

  • E.H. Land, “Color vision and the natural image. Part III: Recent advances in Retinex theory and some implications for cortical computations,” Proc. Natl. Acad. Sci. U.S.A. 80: 5163–5169, 1983.

    Google Scholar 

  • E.H. Land, “Recent advances in Retinex theory,” In D. Ottoson and Z. Zeki (eds.), Central and Peripheral Mechanisms of Colour Vision. Macmillan: New York, 1985.

    Google Scholar 

  • E.H. Land, “Recent advances in Retinex theory,” Vision Research 26: 7–21 1986.

    Google Scholar 

  • E.H. Land and J.J. McCann, “Lightness and Retinex theory,” J. Opt. Soc. Amer. 61 (1): 1–11, 1971.

    Google Scholar 

  • H.-C. Lee, “Method for computing the seene-illuminant chromaticity from specular highlights,” J. Opt. Soc. Amer. A 3: 1694–1699, 1986.

    Google Scholar 

  • R. Luther, “Aus dem Gebiet der Fabreizmetrik,” Z. Techn. Phys. 12: 540–558, 1921.

    Google Scholar 

  • L.T. Maloney, “Computational approaches to color constancy.” Ph.D. dissertation, Stanford University, Stanford, CA, 1984.

  • L.T. Maloney, “Evaluation of linear models of surface spectral reflectance with small numbers of parameters,” J. Opt. Soc. Amer. A 3 (10): 1673–1683, 1986.

    Google Scholar 

  • L.T. Maloney and B.A. Wandell, “A computational model of color constancy,” J. Opt. Soc. Amer. A. 1: 29–33, 1986.

    Google Scholar 

  • J.J. McCann, S.P. McKee, and Taylor, “Quantitative studies in Retinex theory,” Vision Research 16: 445–458, 1976.

    Google Scholar 

  • N. Nyberg, “Zum Aufbau des Farbkoerpers im Raume aller Lichtempfindungen,” Z. Phys. 52: 506–419, 1928.

    Google Scholar 

  • P. Sallstrom, “Colour and physics: some remarks concerning the physical aspects of human colour vision,” University of Stockholm: Institute of Physics Report 73-09, 1973.

  • W.S. Stiles, G. Wyszecki, and N. Ohta, “Counting metameric objectcolor stimuli using frequency limited spectral reflectance function,” J. Opt. Soc. Amer. 67 (6): 779–784, 1977.

    Google Scholar 

  • B.A. Wandell, “The synthesis and analysis of color images,” IEEE Trans. PAMI 9 (1): 2–13, 1987.

    Google Scholar 

  • G. West and M.H. Brill, “Necessary and sufficient conditions for von Kries chromatic adaptation to give color constancy,” J. Math. Biol. 15: 249–258, 1982.

    Google Scholar 

  • J.R. Woodwark and K.M. Quinlan, “Reducing the effect of complexity on volume model evaluation,” Comput.-Aided Design J. 14 (2), 1984.

  • J.A. Worthey, “Limitations of color constancy,” J. Opt. Soc. Amer. A 2 (7): 1014–1026, 1985.

    Google Scholar 

  • J.A. Worthey and M.H. Brill, “Heuristic analysis of von Kries color constancy,” J. Opt. Soc. Amer. A 3 (10): 1708–1712, 1986.

    Google Scholar 

  • G. Wyszecki and W.S. Stiles, Color Science: Concepts, and Methods, Qualitative Data and Formulae. J. Wiley: New York, 1982.

    Google Scholar 

  • G. Wyszecki and W.S. Stiles, “High-level trichromatic colour matching and the pigment bleaching hypothesis, Vision Research 20: 23–37, 1980.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

The author acknowledges the support of the Rhodes Trust and of Magdalen College, Oxford.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Forsyth, D.A. A novel algorithm for color constancy. Int J Comput Vision 5, 5–35 (1990). https://doi.org/10.1007/BF00056770

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00056770

Keywords

Navigation