基于修正多重三角不等式的矢量量化快速搜索算法

C. H. Wu, Hsung-Pin Chang, Y. C. Liu, G. H. Lee, L. Chi
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引用次数: 0

摘要

为了进一步减少候选编码向量的搜索次数,本文提出了一种改进的多重三角不等式消除算法(MMTIE)。MMTIE采用与MTIE方案相同的原始搜索空间,采用初始索引码分配(initial Index Code Assignment, IICA)选择的初始最匹配码向量,并融合候选码向量群(Candidate codevector Group, CCG)方案的交集规则,进一步缩小搜索空间,在编码阶段通过表查找操作找到最匹配的候选码向量。由于IICA方法通过利用相邻块的相关性来选择初始最匹配的编码向量,并且从离线阶段获得预定义的CCG空间,因此MMTIE算法以额外的内存为代价获得了比原始MTIE更好的编码效率。此外,该算法具有与全搜索方法相同的编码质量。实验结果表明,该方案与之前的MTIE编码方案相比是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast-searching algorithm for vector quantization using modified multiple triangular inequality
This paper proposes a Modified Multiple Triangular Inequality Elimination (MMTIE) to further reduce the search number of candidate codevectors. The MMTIE adopts the same original search space as the MTIE scheme with the initial best-matched codevector selected by the Initial Index Code Assignment (IICA), and integrates the intersection rule of the Candidate Codevectors Group (CCG) scheme to further reduce the search space and find the best-matched candidate by table look-up operation in the coding stage. Since the IICA approach selects an initial best-matched codevector by exploiting the correlations of the neighboring blocks and the predefined CCG space is obtained from the off-line stage, the MMTIE algorithm achieves better coding efficiency than the original MTIE at a cost of extra memory. In addition, the proposed algorithm provides the same coding quality as the full search method. Experimental results demonstrate the effectiveness of the proposed scheme in comparison with our previous MTIE coding scheme.
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