Approaching ideal observer efficiency in using color to retrieve information from natural scenes

Journal of the Optical Society of America A: Optics and Image Science, and Vision

Volumn 26, Issue 11, 2009, Pages

  Foster, David H ^a   Marín Franch, Iván ^a,c   Amano, Kinjiro ^a   Nascimento, Sérgio M C ^b  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b UNIVERSITY OF MINHO   (Portugal)

^c UNIVERSITY OF TURIN   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

COLOR; DAYLIGHT SIMULATION; GAUSSIAN NOISE (ELECTRONIC); IMAGE CODING; QUALITY ASSURANCE; REDUNDANCY;

COLOR SIGNALS; CORRELATED COLOR TEMPERATURE; EFFICIENCY LEVELS; GAUSSIAN NOISE; HYPER-SPECTRAL IMAGES; IDEAL OBSERVERS; IMAGE PAIRS; NATURAL SCENES;

INFORMATION USE;

EID: 70449725261     PISSN: 10847529     EISSN: 15208532     Source Type: Journal    
DOI: 10.1364/JOSAA.26.000B14     Document Type: Article

References (46)

1. G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).
2. D. H. Foster, S. M. C. Nascimento, and K. Amano, "Information limits on neural identification of colored surfaces in natural scenes," Visual Neurosci. 21, 331-336 (2004).
3. D. H. Foster, S. M. C. Nascimento, and K. Amano, "Information limits on identification of natural surfaces by apparent colour," Perception 34, 1003-1008 (2005).
4. W. S. Geisler, "Visual perception and the statistical properties of natural scenes," Annu. Rev. Psychol. 59, 167-192 (2008).
5. N. J. Dominy, J.-C. Svenning, and W.-H. Li, "Historical contingency in the evolution of primate color vision," J. Human Evolution 44, 25-45 (2003).
6. C. E. Shannon, "A mathematical theory of communication," [part 1] Bell Syst. Tech. J. 27, 379-423 (1948).
7. C. E. Shannon, "A mathematical theory of communication," [part 2] Bell Syst. Tech. J. 27, 623-656 (1948).
8. T. M. Cover and J. A. Thomas, Elements of Information Theory (Wiley, 1991).
9. G. Buchsbaum and A. Gottschalk, "Trichromacy, opponent colours coding and optimum colour information transmission in the retina," Proc. R. Soc. London, Ser. B 220, 89-113 (1983).
10. J. A. Swets, W. P. Tanner, Jr., and T. G. Birdsall, "Decision processes in perception," Psychol. Rev. 68, 301-340 (1961).
11. N. A. Macmillan and C. D. Creelman, Detection Theory: A User's Guide, 2nd ed. (Erlbaum, 2005).
12. D. H. Foster, K. Amano, S. M. C. Nascimento, and M. J. Foster, "Frequency of metamerism in natural scenes," J. Opt. Soc. Am. A 23, 2359-2372 (2006).
13. M. Vorobyev and D. Osorio, "Receptor noise as a determinant of colour thresholds," Proc. R. Soc. London, Ser. B 265, 351-358 (1998).
14. D. I. A. MacLeod and T. von der Twer, "The pleistochrome: optimal opponent codes for natural colours," in Colour Perception: Mind and the Physical World, R. Mausfeld and D. Heyer, eds. (Oxford Univ. Press, 2003), pp. 155-184.
15. D. H. Foster and R. S. Snelgar, "Test and field spectral sensitivities of colour mechanisms obtained on small white backgrounds: action of unitary opponent-colour processes?" Vision Res. 23, 787-797 (1983).
16. G. D. Finlayson, M. S. Drew, and B. V. Funt, "Spectral sharpening: sensor transformations for improved color constancy," J. Opt. Soc. Am. A 11, 1553-1563 (1994).
17. R. L. De Valois, N. P. Cottaris, S. D. Elfar, L. E. Mahon, and J. A. Wilson, "Some transformations of color information from lateral geniculate nucleus to striate cortex," Proc. Natl. Acad. Sci. U. S. A. 97, 4997-5002 (2000).
18. J. von Kries, "Theoretische Studien über die Umstimmung des Sehorgans," in Festschrift der Albrecht-Ludwigs-Universität (Freiburg, 1902), pp. 145-158.
19. J. von Kries, "Die Gesichtsempfindungen," in Handbuch der Physiologie des Menschen, W. Nagel, ed. (Vieweg, 1905), pp. 109-282.
20. M. A. Webster and J. D. Mollon, "Adaptation and the color statistics of natural images," Vision Res. 37, 3283-3298 (1997).
21. M. Studený and J. Vejnarová, "The multi-information function as a tool for measuring stochastic dependence," in Learning in Graphical Models, M. I. Jordan, ed. (MIT Press, 1999), pp. 261-298.
22. I. Marín-Franch and D. H. Foster, "Distribution of information within and across colour spaces," in CGIV 2008 (Society for Imaging Science and Technology, 2008), pp. 303-306.
23. K. Amano and D. H. Foster, "Colour constancy under simultaneous changes in surface position and illuminant," Proc. R. Soc. London, Ser. B 271, 2319-2326 (2004).
24. A. Lapidoth, "Nearest neighbor decoding for additive non-Gaussian noise channels," IEEE Trans. Inf. Theory 42, 1520-1529 (1996).
25. H. Barlow, "Redundancy reduction revisited," Network Comput. Neural Syst. 12, 241-253 (2001).
26. G. D. Finlayson, M. S. Drew, and B. V. Funt, "Color constancy: generalized diagonal transforms suffice," J. Opt. Soc. Am. A 11, 3011-3019 (1994).
27. B. Funt and H. Jiang, "Non-von-Kries 3-parameter color prediction," Proc. SPIE 5007, 182-189 (2003).
28. D. H. Foster and K. Żychaluk, "Is there a better non-parametric alternative to von Kries scaling?" in CGIV 2008 (Society for Imaging Science and Technology, 2008), pp. 41-44.
29. S. M. C. Nascimento, F. P. Ferreira, and D. H. Foster, "Statistics of spatial cone-excitation ratios in natural scenes," J. Opt. Soc. Am. A 19, 1484-1490 (2002).
30. CIE, "Colorimetry, 3rd Edition," CIE Publication 15:2004 (CIE Central Bureau, Vienna, 2004).
31. D. B. Judd, D. L. MacAdam, and G. Wyszecki, "Spectral distribution of typical daylight as a function of correlated color temperature," J. Opt. Soc. Am. 54, 1031-1040 (1964).
32. J. Hernández-Andrés, J. Romero, and J. L. Nieves, "Color and spectral analysis of daylight in southern Europe," J. Opt. Soc. Am. A 18, 1325-1335 (2001).
33. A. Stockman, L. T. Sharpe, and C. Fach, "The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches," Vision Res. 39, 2901-2927 (1999).
34. A. Stockman and L. T. Sharpe, "The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype," Vision Res. 40, 1711-1737 (2000).
35. B. W. Silverman, Density Estimation for Statistics and Data Analysis (Chapman & Hall, London, 1986).
36. A. Kraskov, H. Stögbauer, and P. Grassberger, "Estimating mutual information," Phys. Rev. E 69, 066138 (2004).
37. R. Steuer, J. Kurths, C. O. Daub, J. Weise, and J. Selbig, "The mutual information: Detecting and evaluating dependencies between variables," Bioinformatics 18, S231-S240 (2002).
38. J. D. Victor, "Binless strategies for estimation of information from neural data," Phys. Rev. E 66, 051903 (2002).
39. L. F. Kozachenko and N. N. Leonenko, "Sample estimate of the entropy of a random vector," Probl. Inf. Transm. 23, 95-101 (1987);
40. Russian translation, Probl. Peredachi Inf. 23, 9-16 (1987).
41. M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. Novi Inverardi, "A new class of random vector entropy estimators and its applications in testing statistical hypotheses," J. Nonparametric Statistics 17, 277-297 (2005).
42. I. Marín-Franch, "Information-theoretic analysis of trichromatic images of natural scenes under different phases of daylight," Ph. D. thesis (The University of Manchester, Manchester, 2009).
43. P. Grassberger, "Entropy estimates from insufficient samplings," (2008), retrieved http://arxiv.org/abs/physics/0307138v2.
44. W. S. Cleveland, "Robust locally weighted regression and smoothing scatterplots," J. Am. Stat. Assoc. 74, 829-836 (1979).
45. J. J. M. Granzier, E. Brenner, and J. B. J. Smeets, "Reliable identification by color under natural conditions," J. Vision 9, 1-8 (2009).
46. D. H. Foster, K. Amano, and S. M. C. Nascimento, "Color constancy in natural scenes explained by global image statistics," Visual Neurosci. 23, 341-349 (2006). (Pubitemid 46024711)