Abstract
The range of contrasts in natural scenes is generally thought to far exceed the limited dynamic ranges of individual contrast-encoding neurons in the primary visual cortex. The visual system may employ gain-control mechanisms () to compensate for the mismatch between the range of natural contrast energies and the limited dynamic range of visual neurons; one proposed mechanism is contrast normalisation or non-specific suppression (). This paper aims to evaluate the role of contrast normalisation in human contrast perception, using a computer model of primary visual cortex. The model uses orthogonal pairs of Gabor patches to simulate simple-cell receptive-fields to calculate local, band-limited contrast in a series of 50 digitised photographs of natural scenes. The average range of contrast energies in each image was 2.29 log units, while the “lifetime range” each model simple cell would see across all images was 2.98 log units. These ranges are greater than the dynamic range of real mammalian simple cells. Contrast normalisation (dividing contrast responses by the summed responses of all nearby neurons) reduces contrast ranges, perhaps sufficiently to match them to neurons' limited dynamic ranges. Comparison of images taken under diffuse and direct lighting conditions showed that contrast normalisation can sometimes match these conditions effectively. This may lead to perceptual contrast constancy in the face of spurious changes in contrast caused by natural environmental conditions.
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