A High-Speed Closest Codeword Search Algorithm for Vector Quantization Using the Pyramid Structure of Codewords
A High-Speed Closest Codeword Search Algorithm for Vector Quantization Using the Pyramid Structure of Codewords
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DOI：
10.11371/iieej.34.653
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
A. Swilem;K. Imamura;H. Hashimoto
中科院分区：
文献类型：
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作者：
A. Swilem;K. Imamura;H. Hashimoto
无论在编码还是码本设计中，用于图像压缩的矢量量化（VQ）都需要花费大量的时间来找到最接近的码字。本文提出了一种高速最接近码字搜索算法，适用于包括熵约束矢量量化（ECVQ）在内的VQ编码和码本设计。通过使用更轻的修正失真度量，我们提出了合适的训练向量和码字拓扑结构，以消除搜索过程中不必要的匹配操作。该算法可以显著加快码本设计过程。给出了基于图像块数据的实验结果。这些结果证实了算法的有效性。
< Summary> 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.