The perspective image of an obliquely inclined textured surface exhibits shape and density distortions of texture elements which allow a human observer to estimate the inclination angle of the surface. However, since the work of Gibson (1950) it has been known that, in the absence of other cues, humans tend to underestimate the slant angle of the surface, particularly when the texture is perceived as being "irregular." The perspective distortions which affect texture elements also shift the projected spatial frequencies of the texture in systematic ways. Using a suitable local spectral filter to measure these frequency gradients, the inclination angle of the surface may be estimated. A computational model has been developed which performs this task using distributions of outputs from filters found to be a good description of simple cell receptive fields. However, for "irregular" textures the filter output distributions are more like those of regular textures at shallower angles of slant, leading the computational algorithm to underestimate the slant angle. This behavioral similarity between human and algorithm suggests the possibility that a similar visual computation is performed in cortex.