Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Color brings relief to human vision

Abstract

In natural scenes, chromatic variations, and the luminance variations that are aligned with them, mainly arise from surfaces such as flowers or painted objects. Pure or near-pure luminance variations, on the other hand, mainly arise from inhomogeneous illumination such as shadows or shading. Here, I provide evidence that knowledge of these color–luminance relationships is built into the machinery of the human visual system. When a pure-luminance grating is added to a differently oriented chromatic grating, the resulting 'plaid' appears to spring into three-dimensional relief, an example of 'shape-from-shading'. By psychophysical measurements, I found that the perception of shape-from-shading in the plaid was triggered when the chromatic and luminance gratings were not aligned, and suppressed when the gratings were aligned. This finding establishes a new role for color vision in determining the three-dimensional structure of an image: one that exploits the natural relationships that exist between color and luminance in the visual world.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2: Shape-from-shading in plaid stimuli.
Figure 3: Stimulus arrangement for the measurement of perceived depth.
Figure 4: Stimulus manipulations (bottom) and results (top) for the first experiment.
Figure 5: Stimulus manipulations and results for the second experiment.
Figure 6: Plaids used in the third experiment.
Figure 7: Stimulus manipulations and results for the third experiment.

Similar content being viewed by others

References

  1. Lu, C. & Fender, D.H. The interaction of color and luminance in stereoscopic vision. Invest. Ophthalmol. 11, 482–489 (1972).

    CAS  PubMed  Google Scholar 

  2. Gregory, R.L. Vision with isoluminant color contrast: a projection technique and observations. Perception 6, 113–119 (1977).

    Article  CAS  Google Scholar 

  3. Ramachandran, V.S. & Gregory, R.L. Does color provide an input to motion perception? Nature 275, 55–56 (1978).

    Article  CAS  Google Scholar 

  4. Rubin, J.M. & Richards, W.A. Color vision and image intensities: When are changes material? Biol. Cybern. 45, 215–226 (1982).

    Article  CAS  Google Scholar 

  5. Livingstone, M.S. & Hubel, D.H. Psychophysical evidence for separate channels for the perception of form, color, movement, and depth. J. Neurosci. 7, 3416–3468 (1987).

    Article  CAS  Google Scholar 

  6. Cavanagh, P. Vision at equiluminance. in Vision and Visual Dysfunction: Limits of Vision Vol. 5. (eds. Kulikowski, J.J., Murray, I.J. & Walsh, V.) 234–250 (CRC Press, Boca Raton, Florida, 1991).

    Google Scholar 

  7. Mullen, K.T. & Kingdom, F.A.A. Color contrast in form perception. in Vision and Visual Dysfunction: the Perception of Color Vol. 6. (eds. Gouras, P. & Cronly-Dillon, J.) 198–217 (Macmillan, Oxford, 1991).

    Google Scholar 

  8. Mollon, J.D. 'Tho' she kneel'd in that place where they grew...' The uses and origins of primate color vision. J. Exp. Biol. 146, 21–38 (1989).

    CAS  Google Scholar 

  9. Regan, D. Human Perception of Objects (Sinauer, Sunderland, Massachusetts, 2000).

    Google Scholar 

  10. Kingdom, F.A.A. & Simmons, D.R. The relationship between color vision and stereoscopic depth perception. J. Soc. 3D Broadcast. Imaging 1, 10–19 (2000).

    Google Scholar 

  11. Sumner, P. & Mollon, J.D. Catarrhine photopigments are optimised for detecting targets against a foliage background. J. Exp. Biol. 23, 1963–1986 (2000).

    Google Scholar 

  12. Gegenfurtner, K.R. & Rieger, J. Sensory and cognitive contributions of color to the recognition of natural scenes. Curr. Biol. 10, 805–808 (2000).

    Article  CAS  Google Scholar 

  13. Domini, N.J. & Lucas, P.W. Ecological importance of trichromatic vision to primates. Nature 410, 363–365 (2001).

    Article  Google Scholar 

  14. Fine, I., MacLeod, D.L.A. & Boynton, G.M. Surface segmentation based on the luminance and color statistics of natural scenes. J. Opt. Soc. Amer. A (in press).

  15. Parraga, C.A., Troscianko, T. & Tolhurst, D.J. Spatiochromatic properties of natural images and human vision. Curr. Biol. 12, 483–487 (2002).

    Article  CAS  Google Scholar 

  16. Ramachandran, V.S. Perception of shape from shading. Nature 331, 163–166 (1988).

    Article  CAS  Google Scholar 

  17. Johnstone, A., Hill, H. & Carman, N. Recognising faces: effects of lighting direction, inversion and brightness reversal. Perception 21, 365–375 (1992).

    Article  Google Scholar 

  18. Sun, J. & Perona, P. Shading and stereo in early perception of shape and reflectance. Perception 26, 519–529 (1997).

    Article  CAS  Google Scholar 

  19. Lehky, S.R. & Sejnowski, T.J. Network model of shape-from-shading: neural function arises from both receptive and projective fields. Nature 333, 452–454 (1988).

    Article  CAS  Google Scholar 

  20. Attick, J.J., Griffin, P.A. & Redlich, A.N. Statistical approach to shape from shading: reconstruction of three-dimensional face surfaces from single two-dimensional images. Neural Comput. 8, 1321–1340 (1996).

    Article  Google Scholar 

  21. Switkes, E., Bradley, A. and DeValois, K.K. Contrast dependence and mechanisms of masking interactions among chromatic and luminance gratings. J. Opt. Soc. Amer. A 5, 1149–1162 (1988).

    Article  CAS  Google Scholar 

  22. Cavangh, P., & Leclerc, Y. Shape from shadows. J. Exp. Psychol. Hum. Percept. Perform. 15, 3–27 (1989).

    Article  Google Scholar 

  23. Knill, D.C., Kersten, D. & Mamassian, P. Implications of a Bayesian formulation of visual information for processing for psychophysics. in Perception as Bayesian Inference (eds. Knill, D.C. & Richards, W.) (Cambridge Univ. Press, Cambridge, UK, 1996).

    Chapter  Google Scholar 

  24. Barlow, H.B. & Foldiak, P. Adaptation and decorrelation in the cortex. in The Computing Neuron (ed. Rosenblith, W.A.) 217–234 (MIT Press, Cambridge, Massachusetts, 1989).

    Google Scholar 

  25. Field, F.J. What is the goal of sensory coding? Neural Comput. 6, 559–601 (1994).

    Article  Google Scholar 

  26. Simoncelli, E.P. & Olshausen, B.A. Natural image statistics and neural representation. Annu. Rev. Neurosci. 24, 1193–1216 (2001).

    Article  CAS  Google Scholar 

  27. Knill, D.C. & Richards, W. Perception as Bayesian Inference (eds. Knill, D.C. & Richards, W.) (Cambridge Univ. Press, Cambridge, UK, 1996).

    Book  Google Scholar 

Download references

Acknowledgements

This research was supported by a Canadian Institute of Health Research grant (MOP-11554 to F.K.). Special thanks to D. Field and K. Mullen for suggestions on an earlier version of the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Frederick A A Kingdom.

Ethics declarations

Competing interests

The author declares no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kingdom, F. Color brings relief to human vision. Nat Neurosci 6, 641–644 (2003). https://doi.org/10.1038/nn1060

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn1060

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing