n通道对称多重描述晶格矢量量化

Jan Østergaard, R. Heusdens, J. Jensen
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引用次数: 19

摘要

我们推导了n通道对称多重描述晶格矢量量化器中中心和侧量化器的解析表达式,在高分辨率假设下,最小化了给定丢包概率的侧描述受熵约束的预期失真。中心量化器的性能与晶格无关,而侧量化器的性能与晶格无关。事实上,侧量化子的归一化秒矩是由l维球面的秒矩给出的。此外,我们的分析结果揭示了一种确定最佳描述数量的简单方法。我们通过数值实验验证了理论结果,并表明在丢包概率为5%的情况下,当使用15位/维的总比特预算和使用三种描述来量化二维单位方差高斯源时,可以在最先进的双描述系统上获得9.1 dB的MSE增益。在丢包20%的情况下,一个类似的实验显示,当使用四种描述时,MSE降低了10.6 dB。
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n-channel symmetric multiple-description lattice vector quantization
We derive analytical expressions for the central and side quantizers in an n-channel symmetric multiple-description lattice vector quantizer which, under high-resolution assumptions, minimize the expected distortion subject to entropy constraints on the side descriptions for given packet-loss probabilities. The performance of the central quantizer is lattice dependent whereas the performance of the side quantizers is lattice independent. In fact the normalized second moments of the side quantizers are given by that of an L-dimensional sphere. Furthermore, our analytical results reveal a simple way to determine the optimum number of descriptions. We verify theoretical results with numerical experiments and show that with a packet-loss probability of 5%, a gain of 9.1 dB in MSE over state-of-the-art two-description systems can be achieved when quantizing a two-dimensional unit-variance Gaussian source using a total bit budget of 15 bits/dimension and using three descriptions. With 20% packet loss, a similar experiment reveals an MSE reduction of 10.6 dB when using four descriptions.
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