A fuzzy entropy-constrained vector quantizer design algorithm and its applications to image coding

In this paper, a novel variable-rate vector quantizer (VQ) design algorithm using fuzzy clustering technique is presented. The algorithm, termed fuzzy entropy-constrained VQ (FECVQ) design algorithm, has a better rate-distort ion performance than that of the usual entropy-constrained VQ (ECVQ) algori thm for variable-rate VQ design. When performing the fuzzy clustering, the FECVQ algorithm considers both the usual squared-distance measure, and the length of channel index associated with each codeword so that the average r ate of the VQ can be controlled. In addition, the membership function for a chieving the optimal clustering for the design of FECVQ are derived. Simula tion results demonstrate that the FECVQ can be an effective alternative for the design of variable-rate VQs.