Gaussian Rate-Distortion-Perception Coding and Entropy-Constrained Scalar Quantization
This work provides theoretical analysis of fundamental limits in rate-distortion-perception coding for the Gaussian case, which is incremental to existing information theory research.
This paper investigates bounds on the Gaussian distortion-rate-perception function for two perception measures (Kullback-Leibler divergence and squared Wasserstein-2 distance), showing these bounds are nondegenerate and establishing an improved lower bound for the Wasserstein-2 case, while revealing that all bounds are generally not tight in the weak perception constraint regime.
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.