OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Editor: Franco Gori
  • Vol. 28, Iss. 11 — Nov. 1, 2011
  • pp: 2385–2399

Spectral color constancy using a maximum entropy approach

Sandra Skaff and James J. Clark  »View Author Affiliations


JOSA A, Vol. 28, Issue 11, pp. 2385-2399 (2011)
http://dx.doi.org/10.1364/JOSAA.28.002385


View Full Text Article

Enhanced HTML    Acrobat PDF (442 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

This paper proposes a solution to the spectral color constancy problem. The method is based on a statistical model for the surface reflectance spectrum and applies a maximum entropy constraint. Unlike prior methods based on linear models, the solution process does not require a set of basis functions to be defined, nor does it require a database of spectra to be specified in advance. Experiments on simulated and real data show that spectral estimation using the maximum entropy approach is feasible and performs similarly to existing spectral methods in spite of the lower level of a priori information required.

© 2011 Optical Society of America

OCIS Codes
(330.1690) Vision, color, and visual optics : Color
(330.1720) Vision, color, and visual optics : Color vision
(330.4060) Vision, color, and visual optics : Vision modeling

ToC Category:
Vision, Color, and Visual Optics

History
Original Manuscript: January 12, 2011
Revised Manuscript: September 5, 2011
Manuscript Accepted: September 8, 2011
Published: October 31, 2011

Virtual Issues
Vol. 7, Iss. 1 Virtual Journal for Biomedical Optics

Citation
Sandra Skaff and James J. Clark, "Spectral color constancy using a maximum entropy approach," J. Opt. Soc. Am. A 28, 2385-2399 (2011)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-28-11-2385


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. J. J. Clark and S. Skaff, “A spectral theory of color perception,” J. Opt. Soc. Am. A 26, 2488–2502 (2009). [CrossRef]
  2. D. H. Brainard and W. T. Freeman, “Bayesian color constancy,” J. Opt. Soc. Am. A 14, 1393–1411 (1997). [CrossRef]
  3. R. Hall, “Comparing spectral color computation methods,” IEEE Comp. Grap. Appl. 19, 36–45 (1999). [CrossRef]
  4. K. Devlin, A. Chalmers, A. Wilkie, and W. Purgathofer, “Tone reproduction and physically based spectral rendering,” in Computer Graphics Forum (Eurographics, 2002), pp. 101–123.
  5. S. Skaff, T. Arbel, and J. J. Clark, “A sequential Bayesian approach to color constancy using multiple sensors,” Computer Vision and Image Understanding 113, 993–1004 (2009). [CrossRef]
  6. L. T. Maloney and B. A. Wandell, “Color constancy: a method for recovering surface spectral reflectance,” J. Opt. Soc. Am. A 3, 29–33 (1986). [CrossRef] [PubMed]
  7. P. Moon and D. E. Spencer, “Polynomial representation of reflectance curves,” J. Opt. Soc. Am. 35, 597–598 (1945). [CrossRef]
  8. R. Schettini, “Deriving spectral reflectance functions of computer-simulated object colors,” Comput. Graph. Forum 13, 211–217 (1994). [CrossRef]
  9. W. T. Freeman and D. H. Brainard, “Bayesian decision theory, the maximum local mass estimate, and color constancy,” in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 1995), pp. 210–217. [CrossRef]
  10. M. H. Brill, “A device performing illuminant-invariant assessment of chromatic relations,” J. Theor. Biol. 71, 473–478 (1978). [CrossRef] [PubMed]
  11. M. H. Brill, “Further features of the illuminant-invariant trichromatic photosensor,” J. Theor. Biol. 78, 305–308 (1979). [CrossRef] [PubMed]
  12. G. West, “Color perception and the limits of color constancy,” J. Math. Biol. 8, 47–53 (1979). [CrossRef] [PubMed]
  13. M. H. Brill and G. West, “Contributions to the theory of invariance of colour under the condition of varying illumination,” J. Math. Biol. 11, 337–350 (1981). [CrossRef]
  14. 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). [CrossRef] [PubMed]
  15. J. von Kries, “Beitrag zur Physiologie der Gesichtsempfinding,” Arch. Anat. Physiol. 2, 5050–5524 (1878).
  16. D. B. Judd, “Hue saturation and lightness of surface colors with chromatic illumination,” J. Opt. Soc. Am. 30, 2–32 (1940). [CrossRef]
  17. J. A. Worthey, “Limitations of color constancy,” J. Opt. Soc. Am. A 2, 1014–1026 (1985). [CrossRef]
  18. G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin Inst. 310, 1–26 (1980). [CrossRef]
  19. R. Gershon, A. D. Jepson, and J. K. Tsotsos, “From [R, G, B] to surface reflectance: computing color constant descriptors in images,” in Proceedings of the International Joint Conference on Artificial Intelligence (AAAI/MIT, 1987), pp. 755–758.
  20. G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulas (Wiley, 1967).
  21. D. B. Judd, D. L. MacAdam, and G. Wyszecky, “Spectral distribution of typical daylight as a function of correlated color temperature,” J. Opt. Soc. Am. 54, 1031–1040 (1964). [CrossRef]
  22. J. Cohen, “Dependency of the spectral reflectance curves of the Munsell color chips,” Psychon. Sci. 1, 369–370 (1964).
  23. L. T. Maloney, “Computational approaches to color constancy,” Ph.D. thesis (Stanford University, 1984).
  24. B. A. Wandell, “The synthesis and analysis of color images,” IEEE Trans. Pattern Anal. Machine Intell. 9, 2–13 (1987). [CrossRef]
  25. A. Yuille, “A method for computing spectral reflectance,” Biol. Cybern. 56, 195–201 (1987). [CrossRef] [PubMed]
  26. M. D’Zmura and P. Lennie, “Mechanisms of color constancy,” J. Opt. Soc. Am. A 3, 1662–1672 (1986). [CrossRef] [PubMed]
  27. M. D. D’Zmura, “Color constancy: surface color from changing illumination,” J. Opt. Soc. Am. A 9, 490–493 (1992). [CrossRef]
  28. M. D. D’Zmura and G. Iverson, “Color Constancy II. Results for two-stage linear recovery of spectral descriptions for lights and surfaces,” J. Opt. Soc. Am. A 10, 2166–2180 (1993). [CrossRef]
  29. M. D. D’Zmura and G. Iverson, “Color Constancy I. Basic theory of two-stage linear recovery of spectral descriptions for lights and surfaces,” J. Opt. Soc. Am. A 10, 2148–2165 (1993). [CrossRef]
  30. M. D. D’Zmura and G. Iverson, “Color Constancy III. General linear recovery of spectral descriptions for lights and surfaces,” J. Opt. Soc. Am. A 11, 2389–2400 (1994). [CrossRef]
  31. J. Ho, B. V. Funt, and M. S. Drew, “Separating a color signal into illumination and surface reflectance components: theory and applications,” IEEE Trans. Pattern Anal. Machine Intell. 12, 966–977 (1990). [CrossRef]
  32. S. Skaff, T. Arbel, and J. J. Clark, “Active Bayesian color constancy with non-uniform sensors,” in Proceedings of the IEEE International Conference on Pattern Recognition (IEEE, 2002), pp. 681–684.
  33. S. Skaff, “Active Bayesian color constancy with non-uniform sensors,” master’s thesis (McGill University, 2002).
  34. E. T. Jaynes, “Prior probabilities,” IEEE Trans. Syst. Sci. Cyber. 4, 227–241 (1968). [CrossRef]
  35. J. J. Clark and S. Skaff, “Maximum entropy models of surface reflectance spectra,” in Proceedings of the IEEE Instrumentation and Measurement Technology Conference (IEEE, 2005), pp. 1557–1560. [CrossRef]
  36. W. S. Stiles and G. Wyszecki, “Counting metameric object colors,” J. Opt. Soc. Am. 52, 313–322 (1962). [CrossRef]
  37. P. Morovic and G. D. Finlayson, “Metamer-set-based approach to estimating surface reflectance from camera RGB,” J. Opt. Soc. Am. A 23, 1814–1822 (2006). [CrossRef]
  38. N. H. Younan, K. Ponnala, and N. Alapati, “Edge detection in multispectral imagery via maximum entropy,” presented at the International Symposium on Remote Sensing of Environment, San José, Costa Rica (25–29 June 2007).
  39. G. D. Finlayson, M. S. Drew, and C. Lu, “Intrinsic images by entropy minimization,” in Proceedings of the European Conference on Computer Vision (Springer, 2004), pp. 582–595.
  40. C. Lu, “Removing shadows from color images,” Ph.D. thesis (School of Computing, Simon Fraser University, 2006).
  41. M. R. Gupta and R. M. Gray, “Color conversions using maximum entropy estimation,” in Proceedings of the IEEE International Conference on Image Processing (IEEE, 2001), pp. 118–121.
  42. B. Jedynak, H. Zheng, M. Daoudi, and D. Barret, “Maximum entropy models for skin detection,” in Proceedings of the IEEE International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (IEEE, 2003), pp. 180–193. [CrossRef]
  43. I. Marin-Franch and D. H. Foster, “Estimating the information available from coloured surfaces in natural scenes,” in Proceedings of the European Conference on Color in Graphics, Imaging and Vision (The Society for Imaging Science and Technology, 2006), pp. 44–47.
  44. E. L. Hall, “TV and color coding,” in Computer Image Processing and Recognition, W.Rheinboldt, ed. (Academic, 1979), pp. 214–239.
  45. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification and Scene Analysis (Wiley, 2001).
  46. M. Hardy, “Entropies of likelihood functions,” in Maximum Entropy and Bayesian Methods, C.R.Smith, G.J.Erickson, and P. O. Neudorfer, eds. (Academic, 1991), pp. 127–130.
  47. M. Toews and T. Arbel, “Entropy-of-likelihood feature selection for image correspondence,” in Proceedings of the IEEE Conference on Computer Vision (IEEE, 2003), pp. 1041–1047. [CrossRef]
  48. S. Skaff and J. J. Clark, “Maximum entropy spectral models for color constancy,” in Proceedings of the Color Imaging Conference (The Society for Imaging Science and Technology, 2007), pp. 100–105.
  49. T. M. Cover and J. A. Thomas, Elements of Information Theory (Wiley, 1991). [CrossRef]
  50. University of Joensuu Color Group, “Spectral database,” http://spectral.joensuu.fi.
  51. J. E. Kaufman, IES Lighting Handbook (Illuminating Engineering Society of North America, 1981).
  52. D. J. Sheskin, Handbook of Parametric and Nonparametric Statistical Procedures (Chapman and Hall, 2000).
  53. Munsell Color Corporation, Munsell Book of Color-Matte Finish Collection (Munsell Color, 1976).
  54. J. P. S. Parkkinen, J. Hallikainen, and T. Jaaskelainen, “Characteristic spectra of Munsell colors,” J. Opt. Soc. Am. A 6, 318–322(1989). [CrossRef]
  55. K. Barnard, “Practical colour constancy,” Ph.D. thesis (School of Computing, Simon Fraser University, 1999).
  56. K. Barnard, V. Cardei, and B. Funt, “A comparison of computational color constancy algorithms. I.: methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11, 972–984 (2002). [CrossRef]
  57. P. V. Gehler, C. Rother, A. Blake, T. Sharp, and T. Minka, “Bayesian color constancy revisited,” in Proceedings of the IEEE International Conference on Computer Vision and Patter Recognition (IEEE, 2008), pp. 1–8.
  58. E. H. Land and J. J. McCann, “Lightness and Retinex theory,” J. Opt. Soc. Am. 61, 1–11 (1971). [CrossRef] [PubMed]
  59. E. H. Land, “The Retinex theory of color vision,” Sci. Am. 237, 108–128 (1977). [CrossRef] [PubMed]
  60. B. K. P. Horn, “Determining lightness from an image,” Comput. Vision Graph. 3, 277–299 (1974).
  61. A. Blake, “Boundary conditions for lightness computation in Mondrian World,” Lect. Notes Comput. Sci. 32, 314–327(1985).
  62. D. H. Brainard and B. A. Wandell, “Analysis of the Retinex theory of color vision,” J. Opt. Soc. Am. A 3, 1651–1661 (1986). [CrossRef] [PubMed]
  63. A. Hurlbert, “Formal connections between lightness algorithms,” J. Opt. Soc. Am. A 3, 1684–1693 (1986). [CrossRef] [PubMed]
  64. G. D. Finlayson, P. M. Hubel, and S. Hordley, “Color by correlation,” in Proceedings of the Fifth Color Imaging Conference (The Society for Imaging Science and Technology, 1997), pp. 6–11.
  65. G. D. Finlayson, S. D. Hordley, and P. M. Hubel, “Color by correlation: a simple unifying framework for color constancy,” IEEE Trans. Pattern Anal. Machine Intell. 23, 1209–1221 (2001). [CrossRef]
  66. G. D. Finlayson, “Color in perspective,” IEEE Trans. Pattern Anal. Machine Intell. 18, 1034–1038 (1996). [CrossRef]
  67. D. A. Forsyth, “A novel algorithm for color constancy,” Int. J. Comput. Vis. 5, 5–36 (1990). [CrossRef]
  68. K. Barnard, “Computational colour constancy: taking theory into practice,” Master’s thesis (School of Computing, Simon Fraser University, 1995).
  69. G. Finlayson and S. Hordley, “Selection for gamut mapping colour constancy,” Image Vis. Comp. 17, 597–604 (1999). [CrossRef]
  70. S. D. Hordley and G. D. Finlayson, “Reevaluation of color constancy algorithm performance,” J. Opt. Soc. Am. A 23, 1008–1020 (2006). [CrossRef]
  71. B. Funt and L. Shi, “The Rehabilitation of MaxRGB,” in Proceedings of the Eighteenth Color Imaging Conference (The Society for Imaging Science and Technology, 2010), pp. 256–259.
  72. M. Mosny and B. Funt, “Multispectral color constancy,” in Proceedings of the Color Imaging Conference (The Society for Imaging Science and Technology, 2006), pp. 309–313.

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited