A Neural Network Model of 3-D Lightness Perception

A neural network model of 3-D lightness perception is presented which builds upon the FACADE Theory Boundary Contour Sys(cid:173) tem/Feature Contour System of Grossberg and colleagues. Early ratio encoding by retinal ganglion neurons as well as psychophysi(cid:173) cal results on constancy across different backgrounds (background constancy) are used to provide functional constraints to the theory and suggest a contrast negation hypothesis which states that ratio measures between coplanar regions are given more weight in the determination of lightness of the respective regions.