Volume 8, Number 5, Article 15, Pages 1-23 doi:10.1167/8.5.15 http://journalofvision.org/8/5/15/ ISSN 1534-7362
Trichromatic reconstruction from the interleaved cone mosaic: Bayesian model and the color appearance of small spots
David H. Brainard
Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
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David R. Williams
Center for Visual Science, University of Rochester, Rochester, NY, USA
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Heidi Hofer
College of Optometry, University of Houston, Houston, TX, USA
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Abstract

Observers use a wide range of color names, including white, to describe monochromatic flashes with a retinal size comparable to that of a single cone. We model such data as a consequence of information loss arising from trichromatic sampling. The model starts with the simulated responses of the individual L, M, and S cones actually present in the cone mosaic and uses these to reconstruct the L-, M-, and S-cone signals that were present at every image location. We incorporate the optics and the mosaic topography of individual observers, as well as the spatio-chromatic statistics of natural images. We simulated the experiment of H. Hofer, B. Singer, & D. R. Williams (2005) and predicted the color name on each simulated trial from the average chromaticity of the spot reconstructed by our model. Broad features of the data across observers emerged naturally as a consequence of the measured individual variation in the relative numbers of L, M, and S cones. The model's output is also consistent with the appearance of larger spots and of sinusoidal contrast modulations. Finally, the model makes testable predictions for future experiments that study how color naming varies with the fine structure of the retinal mosaic.

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History
Received August 20, 2007; published May 29, 2008
Citation
Brainard, D. H., Williams, D. R., & Hofer, H. (2008). Trichromatic reconstruction from the interleaved cone mosaic: Bayesian model and the color appearance of small spots. Journal of Vision, 8(5):15, 1-23, http://journalofvision.org/8/5/15/, doi:10.1167/8.5.15.
Keywords
color appearance/constancy, computational modeling, photoreceptors, structure of natural images
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