Human wavelength discrimination of monochromatic light explained by optimal decoding
Human wavelength discrimination of monochromatic light explained by optimal decoding.
Abstract: We show that human ability to discriminate the wavelength of monochromatic light can be understood as a maximum likelihood decoding of the absorptions by the cones, with a signal processing efficiency that is independent of the wavelength. This work is built on the framework of ideal observer
analysis of visual discrimination used in many previous works. It
additionally highlights a perceptual confound that observers should confuse a change in input light wavelength with a change in input intensity. Hence a simple ideal observer model which assumes that an observer has a full knowledge of input intensity should over-estimate human ability in discriminating colors of two inputs of unequal intensity. This confound also makes it difficult to consistently measure human ability in wavelength discrimination by asking observers to distinguish two input colors while matching their brightness. We identify the experimental method for reliable measurements of discrimination thresholds as the one of Pokorny and Smith (1970) in which observers only need to distinguish two inputs regardless of whether they differ in hue or brightness.
We mathematically formulate wavelength discrimination under this wavelength-intensity confound and show a good agreement between our theoretical prediction and the behavioral data. Our analysis explains why the discrimination threshold varies with the input wavelength, and shows how sensitively the threshold depends on the relative densities of the three types of cones in the retina (and in particular predict discriminations in dichromats).
Our mathematical formulation and solution can be applied to general problems of sensory discrimination when there is a perceptual confound from other sensory feature dimensions.
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