MULTICHANNEL TEXTURE ANALYSIS USING LOCALIZED SPATIAL FILTERS

A computational approach for analyzing visible textures is described. Textures are modeled as irradiance patterns containing a limited range of spatial frequencies, where mutually distinct textures differ significantly in their dominant characterizing frequencies. By encoding images into multiple narrow spatial frequency and orientation channels, the slowly-varying channel envelopes (amplitude and phase) are used to segregate textural regions of different spatial frequency, orientation, or phase characteristics. Thus, an interpretation of image texture as a region code, or carrier of region information, is emphasized. The channel filters used, known as the 2-D Gabor functions, are useful for these purposes in several senses: they have tunable orientation and radial frequency bandwidths, tunable center frequencies, and optimally achieve joint resolution in space and in spatial frequency. By comparing the channel amplitude responses, boundaries between textures can be detected. By locating large variations in the channel phase responses, discontinuities in texture phase can be detected. Examples are given of both types of texture processing using a variety of real and synthetic textures. © 1990 IEEE.