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arXiv 0909.3135cs.ITmath.IT
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一个随机变量替换引理及其在多描述编码中的应用

A Random Variable Substitution Lemma With Applications to Multiple Description Coding

Jia Wang, Jun Chen, Lei Zhao, Paul Cuff, Haim Permuter

摘要:

我们建立了一个随机变量替换引理,并使用它来研究细化层在多描述编码中的作用,阐明了几个现有的可实现的多描述率失真区域之间的关系。具体地说,它表明,El Gamal覆盖(EGC)区域是等价的EGC* 区域(一个先行版本的EGC区域),而Venkataramani-Kramer-Goyal(VKG)区域(当专用于2-描述的情况下)是等价的Zhang-Berger(ZB)区域。此外,我们证明了多描述编码与个人和层次的失真约束,在VKG方案的层数可以显着减少时,只有某些加权和率的关注。研究了细化层在可分级编码(多描述编码的一种特殊情况)中的作用。

英文摘要:

We establish a random variable substitution lemma and use it to investigate the role of refinement layer in multiple description coding, which clarifies the relationship among several existing achievable multiple description rate-distortion regions. Specifically, it is shown that the El Gamal-Cover (EGC) region is equivalent to the EGC* region (an antecedent version of the EGC region) while the Venkataramani-Kramer-Goyal (VKG) region (when specialized to the 2-description case) is equivalent to the Zhang-Berger (ZB) region. Moreover, we prove that for multiple description coding with individual and hierarchical distortion constraints, the number of layers in the VKG scheme can be significantly reduced when only certain weighted sum rates are concerned. The role of refinement layer in scalable coding (a special case of multiple description coding) is also studied.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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