抄録
Vector quantization (VQ) for image compression requires expensive time to find the closest codeword in both encoding and codebook design. In this paper, we propose a high-speed closest codeword search algorithm applicable to both encoding and codebook design for VQ including entropy-constrained vector quantization (ECVQ). By using a lighter modified distortion measure, we propose an appropriate topological structure of training vectors and codewords to eliminate unnecessary matching operations from the search procedure. This algorithm allows significant acceleration in the codebook design process. Experimental results are presented on image block data. These results confirm the effectiveness of our proposed algorithm.
