The concept of multiresolution analysis on the basis of multichannel filtering in the theory of the early stages of human vision offers suitable methods for pattern recognition. A novel micro-optical multiwavelet element, which has the functions of wavelet filtering, beamsplitting, and self-imaging, has been designed and fabricated for a hybrid texture segmentation processor. All sixteen channel filters process in parallel, using a conventional 2-D correlator. Accordingly, sixteen filtered images sensitive to different scales and orientations are obtained simultaneously as features for texture segmentation. Experimental results and primary applications are presented.