A space-variant filter model of texture segregation: parameter adjustment guided by psychophysical data

This article presents a space-variant version of a standard spatial filter model of texture segregation of the "back-pocket" type (i.e., two filter layers with an intermediate pointwise nonlinearity). The model was tested with psychophysical data from experiments with line textures in which target lines differed in orientation from background lines. The textures were presented briefly and then masked. Segregation performance was evaluated along the horizontal meridian up to retinal eccentricities of about 10 deg. Data are reported from two experiments with different line densities (Kehrer 1989) and two experiments with different orientation contrasts between target lines and background lines (Kehrer 1990). Segregation performance proved to depend strongly on these texture variations, and it peaked several degrees from fixation in all cases. The filter model provided satisfactory predictions of experimental data when model parameters were adjusted appropriately. It is concluded (1) that filter models defined in strictly spatial terms (i.e., without temporal properties) offer a sufficient framework to account for the psychophysical data and (2) that the particular course of the performance curve (i.e., the performance peak outside the central region) must be attributed to the characteristics of second-layer filters.