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 System/Feature ContourSystem of Grossberg and colleagues. Early ratio encoding by retinal ganglion neurons as well as psychophysical resultson 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.