Quadtree Based Variable Rate Oriented Mean Shape-Gain Vector Quantization

Mean shape-gain vector quantization (MSGVQ) is extended to include negative gains and square isometries. Square isometries together with a classi cation technique based on average block intensities enable us to enlarge the MSGVQ codebook size without any additional storage requirements while keeping the complexity of both the codebook generation and the encoding manageable. Variable rate codes are obtained with a quadtree segmentation based on a rate-distortion criterion. Experimental results show that our scheme performs favorably when compared to previous product code techniques or quadtree based VQ methods.