Presents a new vector quantization technique, called predictive residual vector quantization (PRVQ), which combines the concepts of predictive vector quantization (PVQ) and residual vector quantization (RVQ) to implement a high performance VQ scheme with low search complexity. A major task in the PRVQ design is the joint optimization of the vector predictor and the RVQ codebooks. In order to achieve this, a constrained optimization technique is introduced which is compared with a jointly designed technique and a closed loop design technique. Simulation results show the superiority of the proposed PRVQ scheme over the equivalent RVQ, PVQ and an unconstrained VQ scheme. The proposed PRVQ scheme gives the best performance when the predictor and all the stage quantizers are jointly optimized.<>
Predictive residual vector quantization
Proceedings of 1st International Conference on Image Processing ; 1 ; 608-612 vol.1
1994-01-01
442570 byte
Conference paper
Electronic Resource
English
Predictive Residual Vector Quantization
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