Pattern analysis and texture discrimination in the Gabor space

The basic biological principles of nonuniform image representation in the combined frequency-position space are utilized in an approach to image representation and processing. A scheme of image decomposition into optimal localized frequency operators, the so-called Gabor elementary functions which minimize the uncertainty inherent in image representation, is accordingly proposed. Applications to size-invariance and object-separable pattern analysis, localized texture discrimination, and representation by partial information are discussed, illustrating the advantages of the Gabor transform