ADVANCES IN RESIDUAL VECTOR QUANTIZATION - A REVIEW

Advances in residual vector quantization (RVQ) are surveyed. Definitio ns of joint encoder optimality and joint decoder optimality are discus sed, Design techniques for RVQ's with large numbers of stages and gene rally different encoder and decoder codebooks are elaborated and exten ded. Fixed-rate RVQ's, and variable-rate RVQ's that employ entropy cod ing are examined. Predictive and finite state RVQ's designed and integ rated into neural-network based source coding structures are revisited , Successive approximation RVQ's that achieve embedded and refinable c oding are reviewed, A new type of successive approximation RVQ that va ries the instantaneous block rate by using different numbers of stages on different blocks is introduced and applied to image waveforms, and a scalar version of the new residual quantizer is applied to image su bbands in an embedded wavelet transform coding system.