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