Textures in images have a natural order, both in orientation and multiple narrow-band frequency, which requires the user to employ multichannel local spatial/frequency filtering and orientation selectivity, and to have a multiscale characteristic. Each channel covers one part of a whole frequency domain, which indicates different information for the different texton. Gabor filter, as a near orthogonal wavelet used in this paper, has orientation selectivity, multiscale property, linear phase, and good localization both in spatial and frequency domains, which are suitable for texture analysis. Gabor filters are employed for clustering the similarity of the same type of textons. Gaussian filters are also used for detection of normal image edges. Then hybrid texture and nontexture gradient measurement is based on fusion of the difference of amplitude of the filter responses between Gabor and Gaussian filters at neighboring pixels by mainly using average squared gradient. Normalization, based on the noise response and based on maximum response, is computed.
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