Concentric-shell partition vector quantization with application to image coding

Abstract

A method for designing a vector quantizer by first partitioning the residual image vector space into concentric shells and then searching for the smallest possible codebook to represent the residual image vector space, while adhering to the visual perceptive qualities such as edges and textures in the image representation, is described. The coding method involves the decomposition of the image vector into relatively independent components, each with a small dynamic range, to permit the design of a small fixed codebook for the vector quantizer. Optimal partitioning amounts to optimally selecting the set of shell radii, which is achieved using a modified form of simulated annealing. The results obtained in the coding of images show that the concentric-shell partition vector quantizer compares favourably with the gain-shape vector quantizer in terms of subjective image quality at the same bit rate while achieving higher SNR and lower computational complexity. >