A New Partial Codeword Updating Scheme Based on Rate-Distortion Optimization for Adaptive Vector Quantization

In this paper, we propose a new adaptive vector quantization (AVQ) algorithm based on the rate-distortion optimization. This algorithm employs a new partial codeword updating (PCU) scheme which achieves rate-distortion performance superior to that of the conventional AVQ algorithms using the full codeword updating (FCU) scheme. The PCU-AVQ only updates the codeword´s components with the quantization error higher than an optimal threshold instead of replacing the whole codeword. Additionally, the mathematical relation between the Lagrangian multiplier and the approximate optimal threshold is devised to reduce the rate-distortion cost computation. The experimental results show that the proposed PCU-AVQ algorithm indeed improves the rate-distortion performance without much computational complexity penalty. The PCU-AVQ can be combined with transform coding and entropy coding for higher compression ratio, and it can be widely implemented in specific AVQ algorithms for image, video and speech coding.