Gaussian Rate-Distortion-Perception Coding and Entropy-Constrained Scalar Quantization

Li Xie, Liangyan Li, Jun Chen, Lei Yu, Zhongshan Zhang
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Abstract

This paper investigates the best known bounds on the quadratic Gaussian distortion-rate-perception function with limited common randomness for the Kullback-Leibler divergence-based perception measure, as well as their counterparts for the squared Wasserstein-2 distance-based perception measure, recently established by Xie et al. These bounds are shown to be nondegenerate in the sense that they cannot be deduced from each other via a refined version of Talagrand's transportation inequality. On the other hand, an improved lower bound is established when the perception measure is given by the squared Wasserstein-2 distance. In addition, it is revealed by exploiting the connection between rate-distortion-perception coding and entropy-constrained scalar quantization that all the aforementioned bounds are generally not tight in the weak perception constraint regime.
高斯率失真感知编码和熵约束标量量化
本文研究了基于库尔贝克-莱伯勒发散的感知度量的二次高斯和失真率感知函数的已知最佳下限,以及谢文杰等人最近建立的基于平方瓦瑟斯坦-2 距离的感知度量的对应下限。另一方面,当感知度量由平方瓦瑟斯坦-2 距离给出时,建立了一个改进的下界。此外,通过利用速率失真感知编码与熵约束标量量化之间的联系,我们还发现,在弱感知约束条件下,上述所有约束一般都不严格。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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