Efficient Gabor Filter Design Using Rician Output Statistics

Gabor filters have been applied sucessfully to a broad range of multidimensional signal processing and image processing tasks. The present paper considers the design of a single filter to segment a two-texture image. A new efficient algorithm for Gabor-filter design is presented. The algorithm draws upon previous results that showed that the output of a Gabor-filtered texture is well represented by a Rician distribution. The new algorithm uses the Rician model to estimate the output statistics of a pair of sample textures from their windowed autocorrelation functions. A measure of the total output power is used to select the center frequency of the filter and estimate the output statistics. The method is further generalized to include the statistics of post-filtered outputs. Experimental results are presented that demonstrate the efficacy of the algorithms.