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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Editor: Stephen A. Burns
  • Vol. 22, Iss. 10 — Oct. 1, 2005
  • pp: 2060–2071

Stability of the color-opponent signals under changes of illuminant in natural scenes

P. G. Lovell, D. J. Tolhurst, C. A. Párraga, R. Baddeley, U. Leonards, J. Troscianko, and T. Troscianko  »View Author Affiliations


JOSA A, Vol. 22, Issue 10, pp. 2060-2071 (2005)
http://dx.doi.org/10.1364/JOSAA.22.002060


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Abstract

Illumination varies greatly both across parts of a natural scene and as a function of time, whereas the spectral reflectance function of surfaces remains more stable and is of much greater relevance when searching for specific targets. This study investigates the functional properties of postreceptoral opponent-channel responses, in particular regarding their stability against spatial and temporal variation in illumination. We studied images of natural scenes obtained in UK and Uganda with digital cameras calibrated to produce estimated L-, M-, and S-cone responses of trichromatic primates (human) and birds (starling). For both primates and birds we calculated luminance and red–green opponent (RG) responses. We also calculated a primate blue–yellow-opponent (BY) response. The BY response varies with changes in illumination, both across time and across the image, rendering this factor less invariant. The RG response is much more stable than the BY response across such changes in illumination for primates, less so for birds. These differences between species are due to the greater separation of bird L and M cones in wavelength and the narrower bandwidth of the cone action spectra. This greater separation also produces a larger chromatic signal for a given change in spectral reflectance. Thus bird vision seems to suffer a greater degree of spatiotemporal “clutter” than primate vision, but also enhances differences between targets and background. Therefore, there may be a trade-off between the degree of chromatic clutter in a visual system versus the degree of chromatic difference between a target and its background. Primate and bird visual systems have found different solutions to this trade-off.

© 2005 Optical Society of America

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

ToC Category:
Visual Coding and Natural Scene Statistics

History
Original Manuscript: January 31, 2005
Revised Manuscript: April 7, 2005
Manuscript Accepted: April 28, 2005
Published: October 1, 2005

Citation
P. G. Lovell, D. J. Tolhurst, C. A. Párraga, J. Troscianko, T. Troscianko, R. Baddeley, and U. Leonards, "Stability of the color-opponent signals under changes of illuminant in natural scenes," J. Opt. Soc. Am. A 22, 2060-2071 (2005)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-22-10-2060


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References

  1. K. T. Mullen, F. A. A. Kingdom, “Colour contrast in form perception,” in The Perception of Colour, P. Gouras, ed. (Macmillan, 1991), pp. 198–217.
  2. V. V. Maximov, “Environmental factors which may have led to the appearance of colour vision,” Philos. Trans. R. Soc. London, Ser. B 355, 1239–1242 (2000). [CrossRef] [PubMed]
  3. R. L. De Valois, “Analysis and coding of color vision in the primate visual system,” Cold Spring Harbor Symp. Quant. Biol. 30, 567–580 (1965). [CrossRef] [PubMed]
  4. R. L. De Valois, I. Abramov, G. H. Jacobs, “Analysis of response patterns of LGN cells,” J. Opt. Soc. Am. 56, 966–977 (1966). [CrossRef] [PubMed]
  5. R. L. De Valois, K. K. De Valois, “A multistage color model,” Vision Res. 33, 1053–1065 (1993). [CrossRef] [PubMed]
  6. L. M. Hurvich, D. Jameson, “An opponent-process theory of colour vision,” Psychol. Rev. 64, 384–404 (1957). [CrossRef]
  7. G. H. Jacobs, “Primate photopigments and primate color vision,” Proc. Natl. Acad. Sci. U.S.A. 93, 577–581 (1996). [CrossRef] [PubMed]
  8. T. N. Wiesel, D. H. Hubel, “Spatial and chromatic interactions in the lateral geniculate nucleous of the rhesus monkey,” J. Neurophysiol. 29, 1115–1156 (1966). [PubMed]
  9. F. M. De Monasterio, P. Gouras, “Functional properties of ganglion cells of the rhesus monkey retina,” J. Physiol. (London) 251, 167–195 (1975).
  10. D. L. Ruderman, T. W. Cronin, C. C. Chiao, “Statistics of cone responses to natural images: implications for visual coding,” J. Opt. Soc. Am. A 15, 2036–2045 (1998). [CrossRef]
  11. J. D. Mollon, ““Tho she kneeld in that place where they grew.” The uses and origins of primate colour vision,” J. Exp. Biol. 146, 21–38 (1989). [PubMed]
  12. G. D. Finlayson, S. D. Hordley, “Color constancy at a pixel,” J. Opt. Soc. Am. A 18, 253–264 (2001). [CrossRef]
  13. C. C. Chiao, D. Osorio, M. Vorobyev, T. W. Cronin, “Characterization of natural illuminants in forests and the use of digital video data to reconstruct illuminant spectra,” J. Opt. Soc. Am. A 17, 1713–1721 (2000). [CrossRef]
  14. T. Troscianko, J. P. Harris, “Phase discrimination in chromatic gratings,” Perception 15, A18 (1986).
  15. D. Steverding, T. Troscianko, “On the role of blue shadows in the visual behaviour of tsetse flies,” Proc. R. Soc. London, Ser. B 271, S16–S17 (2003). [CrossRef]
  16. A. Olmos, F. A. A. Kingdom, “A biologically inspired algorithm for the recovery of shading and reflectance images,” Perception 33, 1463–1473 (2004). [CrossRef]
  17. M. G. Nagle, D. Osorio, “The tuning of human photopigments may minimize red-green chromatic signals in natural conditions,” Proc. R. Soc. London, Ser. B 252, 209–213 (1993). [CrossRef]
  18. P. Sumner, J. D. Mollon, “Catarrhine photopigments are optimized for detecting targets against a foliage background,” J. Exp. Biol. 203, 1963–1986 (2000). [PubMed]
  19. N. J. Dominy, P. W. Lucas, “Ecological importance of trichromatic vision to primates,” Nature (London) 410, 363–365 (2001). [CrossRef]
  20. B. C. Regan, C. Julliot, B. Simmen, F. Vienot, P. Charles-Dominique, J. D. Mollon, “Fruits, foliage and the evolution of primate colour vision,” Philos. Trans. R. Soc. London, Ser. B 356, 229–284 (2001). [CrossRef] [PubMed]
  21. C. A. Párraga, T. Troscianko, D. J. Tolhurst, “Spatiochromatic properties of natural images and human vision,” Curr. Biol. 12, 483–487 (2002). [CrossRef] [PubMed]
  22. N. S. Hart, J. C. Partridge, I. C. Cuthill, “Visual pigments, oil droplets and cone photoreceptor distribution in the European starling (Sturnus vulgaris),” J. Exp. Biol. 201, 1433–1446 (1998). [PubMed]
  23. D. Osorio, M. Vorobyev, C. D. Jones, “Colour vision of domestic chicks,” J. Exp. Biol. 202, 2951–2959 (1999). [PubMed]
  24. C. A. Párraga, T. Troscianko, D. J. Tolhurst, “Performing a naturalistic visual task when the spatial structure of colour in natural scenes is changed,” Perception 32, Suppl., 168 (2003).
  25. T. Troscianko, C. A. Párraga, U. Leonards, R. J. Baddeley, J. Troscianko, D. J. Tolhurst, “Leaves, fruit, shadows, and lighting in Kibale Forest, Uganda,” Perception 32, Suppl., 51 (2003). [CrossRef]
  26. T. Troscianko, C. A. Párraga, P. G. Lovell, D. J. Tolhurst, R. J. Baddeley, U. Leonards, “Natural illumination, shadows and primate colour vision,” Perception 33, Suppl., 45A (2004).
  27. V. C. Smith, J. Pokorny, “Spectral sensitivity of color-blind observers and the cone photopigments,” Vision Res. 12, 2059–2071 (1972). [CrossRef] [PubMed]
  28. V. C. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm,” Vision Res. 15, 161–171 (1975). [CrossRef] [PubMed]
  29. J. A. Endler, “The color of light in forests and its implications,” Ecol. Monogr. 63, 1–27 (1993). [CrossRef]
  30. L. T. Maloney, B. A. Wandell, “Color constancy: a method for recovering surface spectral reflectance,” J. Opt. Soc. Am. A 3, 29–33 (1986). [CrossRef] [PubMed]
  31. W. S. Stiles, G. Wyszecki, N. Ohta, “Counting metameric object-colour stimuli using frequency-limited spectral reflectance functions,” J. Opt. Soc. Am. 67, 779–784 (1977). [CrossRef]
  32. L. T. Maloney, “Evaluation of linear models of surface spectral reflectance with small numbers of parameters,” J. Opt. Soc. Am. A 3, 1673–1683 (1986). [CrossRef] [PubMed]
  33. J. L. Dannemiller, “Spectral reflectance of natural objects: how many basis functions are necessary?” J. Opt. Soc. Am. A 9, 507–515 (1992). [CrossRef]
  34. D. H. Foster, K. Amano, S. M. C. Nascimento, “Color anisotropy for detecting violations of color constancy in natural scenes under daylight changes,” Invest. Ophthalmol. Visual Sci. 42, Suppl., S720 (2001).
  35. E. K. Oxtoby, D. H. Foster, K. Amano, S. M. C. Nascimento, “How many basis functions are needed to reproduce coloured patterns under illuminant changes?” Perception 31, Suppl., 66 (2002).
  36. V. Cheung, S. Westland, D. Connah, C. Ripamonti, “A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms,” Coloration Technol. 120, 19–25 (2004).
  37. D. Connah, S. Westland, M. G. A. Thomson, “Recovering spectral information using digital camera systems,” Coloration Technol. 117, 309–311 (2001).
  38. G. Hong, M. R. Luo, P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26, 76–84 (2000). [CrossRef]
  39. T. Johnson, “Methods for characterising colour scanners and digital cameras,” Displays 16, 183–191 (1996). [CrossRef]
  40. M. Shi, G. Healey, “Using reflectance models for color scanner calibration,” J. Opt. Soc. Am. A 19, 645–656 (2002). [CrossRef]
  41. S. Westland, C. Ripamonti, Computational Color Science Using Matlab (Wiley, 2004). [CrossRef]
  42. J. Parkkinen, T. Jaaskelainen, M. Kuittinen, “Spectral representation of color images,” presented at the IEEE 9th International Conference on Pattern Recognition, Rome, Italy, November 14–17, 1988.
  43. G. Wyszecki, W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulas (Wiley, 1967), pp. xiv, 628.
  44. P. Sumner, B. C. Regan, J. D. Mollon, “Cambridge database of natural spectra” (2004); http://vision.psychol.cam.ac.uk/spectra/.
  45. D. I. A. MacLeod, R. M. Boynton, “Chromaticity diagram showing cone excitation by stimuli of equal luminance,” J. Opt. Soc. Am. 68, 1183–1187 (1979). [CrossRef]
  46. C. A. Párraga, G. Brelstaff, T. Troscianko, I. R. Moorhead, “Color and luminance information in natural scenes,” J. Opt. Soc. Am. A 15, 563–569 (1998). [CrossRef]
  47. C. A. Párraga, T. Troscianko, D. J. Tolhurst, (2000). “The human visual system is optimised for processing the spatial information in natural visual images,” Curr. Biol. 10, 35–38 (2001). [CrossRef]
  48. M. Vorobyev, m.vorobyev@uq.edu.au (personal communication, 2005).
  49. A. Gilchrist, “Perceived lightness depends on perceived spatial arrangement,” Science 195, 185–187 (1977). [CrossRef] [PubMed]
  50. A. Gilchrist, V. Annan, “Articulation effects in lightness: historical background and theoretical implications,” Perception 31, 141–150 (2002). [CrossRef] [PubMed]
  51. A. C. Smith, H. M. Buchanan-Smith, A. K. Surridge, D. Osorio, N. I. Mundy, “The effect of colour vision status on the detection and selection of fruits by tamarins (Saguinus spp.),” J. Exp. Biol. 206, 3159–3165 (2003). [CrossRef] [PubMed]

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