Nonlinear processes in visual pattern discrimination.

Visual performance on many simple pattern discrimination tasks can be accurately predicted by quasi-linear models composed of oriented linear filters followed by simple contrast nonlinearities. However, many complex discrimination tasks require highly nonlinear processes for their explanation. Evidence is provided for two nonlinear processes in pattern discrimination: (i) one process involves a sequence of filtering, rectification, and subsequent filtering to extract texture boundaries; (ii) the second process results from contrast gain-control processes. It is suggested that quasi-linear processes and nonlinear texture-boundary processes, each with an appropriate contrast gain control, may operate in parallel to provide the basis for all higher-level visual analyses.