实用的多分辨率源编码:TSVQ重访

M. Effros
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引用次数: 27

摘要

考虑用于描述L分辨率的固定源的多分辨率源代码。第一分辨率下的描述以速率R/sub 1/给出,并实现不大于D/sub 1/的预期失真。第二分辨率下的描述包括第一描述和速率R/sub 2/的细化描述,并实现不大于D/sub 2/的预期失真,等等。先前导出的多分辨率源编码边界描述了可实现的速率和失真向量族((R/sub 1/, R/sub 2/,…R/下标L/), (D/下标1/,D/下标2/,D/下标L/))通过研究这些多分辨率率失真边界,我们深入了解了实际的多分辨率信源编码问题。这些见解导致了一种新的基于树结构矢量量化器的多分辨率源代码。本文介绍了该算法、优化设计和初步实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical multi-resolution source coding: TSVQ revisited
Consider a multi-resolution source code for describing a stationary source at L resolutions. The description at the first resolution is given at rate R/sub 1/ and achieves an expected distortion no greater than D/sub 1/. The description at the second resolution includes both the first description and a refining description of rate R/sub 2/ and achieves expected distortion no greater than D/sub 2/, and so on. Previously derived multi-resolution source coding bounds describe the family of achievable rate and distortion vectors ((R/sub 1/, R/sub 2/, ..., R/sub L/), (D/sub 1/, D/sub 2/, D/sub L/)). By examining these multi-resolution rate-distortion bounds, we gain insight into the problem of practical multi-resolution source coding. These insights lead to a new multi-resolution source code based on the tree-structured vector quantizer. This paper covers the algorithm, its optimal design, and preliminary experimental results.
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