Optimum classification in subband coding of images

This paper investigates the classification technique, applied to subband coding of images, as a way of exploiting the non-stationary nature of image subbands. An algorithm for maximizing the classification gain, is presented. Each subband is optimally classified and the classification map is sent as side information. After optimum rate allocation, the classes are encoded using arithmetic and trellis coded quantization (ACTCQ) system. We compare this approach with other approaches for classification proposed in the literature. We propose a method for reducing the side rate which exploits the dependence between subbands as well as the within band dependence