The selective integration neural network model of lightness perception

A new neural network model of 3D lightness perception is presented which builds upon previous models of contrast detection and filling-in. The consideration of a wealth of data suggests that the visual system performs the luminance-to-lightness transformation in a highly context-sensitive manner. In particular we propose that a key component of this transformation is the selective integration of early luminance ratios encoded at the retina. Simulations of the model address recent stimuli by Adelson (1993), White's illusion (1979) and the classic Benary cross, among others.