This paper presents a computational model for color coding that provides a functional explanation of how humans perceive colors in a homogeneous color space. Beginning with known properties of human cone photoreceptors, the model estimates the locations of the reflectance spectra of Munsell color chips in perceptual color space as represented in the CIE L*a*b* color system. The fit between the two structures is within the limits of expected measurement error. Estimates of the structure of perceptual color space for color anomalous dichromats missing one of the normal cone photoreceptors correspond closely to results from the Farnsworth-Munsell color test. An unanticipated outcome of the model provides a functional explanation of why additive lights are always red, green, and blue and provide maximum gamut for color monitors and color television even though they do not correspond to human cone absorption spectra.perceptual color ͉ retina ͉ neuroscience ͉ dichromats T he aim of this article is to formulate a model for color coding that estimates how humans perceive color as a function of their cone sensitivity curves. The model is functional in the sense that it answers some of the how and why questions about color processing raised below. The model is computational in the sense that it provides formulas to predict, among other things, how normal human color perception with three cone photoreceptors differs from human color perception where one cone is missing. We will use the term optimal in the sense that the code carries the maximum amount of information using minimal channel capacity or bandwidth.All visual information used by the brain in processing visual images, including the information about the color of objects, originates in the photoreceptors in the retina. The function of human color vision is to assign the colors of objects in the visual environment to locations in a coherent perceptual color space. The information about the color of an object resides in its reflectance spectra. Color is inferred from light reflected from the surfaces of objects. That light is the product of the reflectance spectrum of the object and the wavelength composition of the illumination. Basically, the retina has to consolidate the information received by many millions of highly redundant wavelength-sensitive photoreceptor cells into an informationefficient and compressed code for transmission through the approximately one million fibers of the optic nerve. The code carrying the visual information down the optic nerve must contain information about the color of objects. We emphasize the fact that the physiological implementation of color coding is beyond the scope of this article. Even though the abstract mathematical calculations of our model implemented by a computer clearly have no physiological analogs, we do think that computations that result in outcomes similar to those of our model are carried out by the human visual system in some fashion. The bandwidth limitations of the optic nerve suggest that much of the color ...