基于多路径树搜索策略的有限状态矢量量化图像/视频编码

S. Juan, Yen Chao, Chen-Yi Lee
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引用次数: 1

摘要

本文提出了一种新的矢量量化(VQ)算法,该算法利用了树搜索和有限状态矢量量化的特点,用于图像/视频编码。在树搜索VQ中,为持续搜索确定多个候选项,以最佳地确定最小失真的索引。此外,为了满足邻树多路径搜索的概念,对期望的码本进行了分层重组,使图像质量平均提高了4 dB。在有限状态VQ中,增加了对状态码本的适应,以提高由树搜索VQ产生的索引的命中率,从而进一步减少压缩位。然后包含一个标识码,以指示哪个输出索引所属。与传统的有限状态和树搜索VQs相比,我们提出的算法不仅达到了更高的压缩比,而且达到了更好的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Finite state vector quantization with multi-path tree search strategy for image/video coding
This paper presents a new vector quantization (VQ) algorithm exploiting the features of tree-search as well as finite state VQs for image/video coding. In the tree-search VQ, multiple candidates are identified for on-going search to optimally determine an index of the minimum distortion. In addition, the desired codebook has been reorganized hierarchically to meet the concept of multi-path search of neighboring trees so that picture quality can be improved by 4 dB on the average. In the finite state VQ, adaptation to the state codebooks is added to enhance the hit-ratio of the index produced by the tree-search VQ and hence to further reduce compressed bits. An identifier code is then included to indicate to which output indices belong. Our proposed algorithm not only reaches a higher compression ratio but also achieves better quality compared to conventional finite-state and tree-search VQs.<>
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