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Hierarchical image sequence coding with tree-structured vector quantization

机译:编码与树结构矢量量化的分层图像序列

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The paper presents two different approaches to image sequence coding which exploit the spatial frequency statistics as well as the spatial and temporal correlation present in the video signal. The first approach is the pyramidal decomposition of the Motion Compensated Frame Difference (MCFD) signal in the frequency domain and the subsequent coding by unbalanced Tree Structured Vector Quantizers (TSVQ) designed to match the statistics of the frequency bands. The type of TSVQ used in this study possess the advantage of low computational complexity with coding performance comparable to full-search vector quantization. The second approach is similar except that the order of motion estimation/compensation and pyramidal decomposition are interchanged.
机译:本文呈现了两种不同的方法对图像序列编码的方法,其利用空间频率统计以及视频信号中存在的空间和时间相关性。第一方法是频域中的运动补偿帧差(MCFD)信号的金字塔分解,并且由不平衡树结构化矢量量化器(TSVQ)的后续编码旨在匹配频带的统计数据。本研究中使用的TSVQ的类型具有低计算复杂性的优点,具有与全搜索矢量量化相当的编码性能。除了互换运动估计/补偿和金字塔分解的顺序之外,第二种方法是类似的。

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