Emergence of unique hues from sparse coding of color in natural scenes
Alexander Belsten, E. Paxon Frady, Bruno A. Olshausen

TL;DR
This study links the perception of unique hues to the statistical properties of natural scenes by demonstrating that sparse coding of cone responses naturally yields the four unique hues, offering insights into their neural basis.
Contribution
It introduces a sparse coding model adapted to natural scene color statistics that reproduces the four unique hues and explains their neural and perceptual properties.
Findings
Sparse coding converges to four unique hues plus black and white.
Nonlinear inference yields excitatory and inhibitory interactions among hues.
Natural scene color statistics are non-Gaussian with heavy tails.
Abstract
Our subjective experience of color is typically described by abstract properties such as hue, saturation, and brightness that do not directly correspond to sensory signals arising from cones in the retina. Along the hue dimension, certain colors -- red, green, blue, and yellow -- appear unique in that they are not perceived as a combination of other colors, and the pairs red-green and blue-yellow appear opposites. However, the anatomical and physiological correlates of these 'unique hues' within the brain and the reason for their existence remain a mystery. Here, we demonstrate a direct connection between these hues and the statistics of the natural visual environment. Analysis of simulated cone responses on a dataset of 503 calibrated natural images reveals a strongly non-Gaussian distribution in 3D color space, with heavy tails in distinct, asymmetrically arranged directions. A sparse…
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Taxonomy
TopicsVisual perception and processing mechanisms · Color perception and design · Multisensory perception and integration
