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In lossy compression, Blau and Michaeli [5] introduced the information rate-distortion-perception (RDP) function, extending traditional rate-distortion theory by incorporating perceptual quality. More recently, this framework was expanded…

Information Theory · Computer Science 2025-04-15 Nam Nguyen , Thinh Nguyen , Bella Bose

In the context of lossy compression, Blau & Michaeli (2019) adopt a mathematical notion of perceptual quality and define the information rate-distortion-perception function, generalizing the classical rate-distortion tradeoff. We consider…

Information Theory · Computer Science 2021-12-23 George Zhang , Jingjing Qian , Jun Chen , Ashish Khisti

We consider causal, low-latency, sequential lossy compression, with mean squared-error (MSE) as the distortion loss, and a perception loss function (PLF) to enhance the realism of reconstructions. As the main contribution, we propose and…

Machine Learning · Computer Science 2025-02-18 Sadaf Salehkalaibar , Buu Phan , Likun Cai , Joao Atz Dick , Wei Yu , Jun Chen , Ashish Khisti

In the theory of lossy compression, the rate-distortion (R-D) function $R(D)$ describes how much a data source can be compressed (in bit-rate) at any given level of fidelity (distortion). Obtaining $R(D)$ for a given data source establishes…

Information Theory · Computer Science 2023-10-31 Yibo Yang , Stephan Eckstein , Marcel Nutz , Stephan Mandt

In this paper we study the problem of characterizing and computing the nonanticipative rate distortion function (NRDF) for partially observable multivariate Gauss-Markov processes with hard mean squared error (MSE) distortion constraints.…

Information Theory · Computer Science 2021-10-22 Photios A. Stavrou , Mikael Skoglund

The rate-distortion-perception (RDP) tradeoff characterizes the fundamental limits of lossy compression by jointly considering bitrate, reconstruction fidelity, and perceptual quality. While recent neural compression methods have improved…

Information Theory · Computer Science 2026-05-25 Yuhan Wang , Suzhi Bi , Ying-Jun Angela Zhang

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…

Information Theory · Computer Science 2024-09-05 Li Xie , Liangyan Li , Jun Chen , Lei Yu , Zhongshan Zhang

We revisit the Gray-Wyner lossy source coding problem and derive the first-order asymptotic optimal rate-distortion-perception region when additional perception constraints are imposed on reproduced source sequences. The optimal trade-off…

Information Theory · Computer Science 2026-01-19 Yu Yang , Yingxin Zhang , Weijie Yuan , Lin Zhou

We characterize the rate-distortion function for zero-mean stationary Gaussian sources under the MSE fidelity criterion and subject to the additional constraint that the distortion is uncorrelated to the input. The solution is given by two…

Information Theory · Computer Science 2008-01-14 Milan S. Derpich , Jan Ostergaard , Graham C. Goodwin

The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of squared error distortion measure. An explicit expression is obtained when both source and…

Information Theory · Computer Science 2024-03-25 Li Xie , Liangyan Li , Jun Chen , Zhongshan Zhang

In this work we study the rate-distortion function (RDF) for lossy compression of asynchronously-sampled continuous-time (CT) wide-sense cyclostationary (WSCS) Gaussian processes with memory. As the case of synchronous sampling, i.e., when…

Information Theory · Computer Science 2024-05-27 Zikun Tan , Ron Dabora , H. Vincent Poor

Recent advances in Rate-Distortion-Perception (RDP) theory highlight the importance of balancing compression level, reconstruction quality, and perceptual fidelity. While previous work has explored numerical approaches to approximate the…

Information Theory · Computer Science 2025-08-20 Chunhui Chen , Linyi Chen , Xueyan Niu , Hao Wu

The lower the distortion of an estimator, the more the distribution of its outputs generally deviates from the distribution of the signals it attempts to estimate. This phenomenon, known as the perception-distortion tradeoff, has captured…

Image and Video Processing · Electrical Eng. & Systems 2021-07-07 Dror Freirich , Tomer Michaeli , Ron Meir

The relation between rate distortion function (RDF) and Bayesian filtering theory is discussed. The relation is established by imposing a causal or realizability constraint on the reconstruction conditional distribution of the RDF, leading…

Information Theory · Computer Science 2012-04-16 Photios A. Stavrou , Charalambos D. Charalambous , Christos K. Kourtellaris

The self-random number generation (SRNG) problem is considered for general setting. In the literature, the optimum SRNG rate with respect to the variational distance has been discussed. In this paper, we first try to characterize the…

Information Theory · Computer Science 2024-02-01 Ryo Nomura

Rate-distortion-perception theory generalizes Shannon's rate-distortion theory by introducing a constraint on the perceptual quality of the output. The perception constraint complements the conventional distortion constraint and aims to…

Information Theory · Computer Science 2022-04-14 Jun Chen , Lei Yu , Jia Wang , Wuxian Shi , Yiqun Ge , Wen Tong

This paper investigates applications of nonanticipative Rate Distortion Function (RDF) in a) zero-delay Joint Source-Channel Coding (JSCC) design based on average and excess distortion probability, b) in bounding the Optimal Performance…

Information Theory · Computer Science 2016-11-17 Photios A. Stavrou , Christos K. Kourtellaris , C. D. Charalambous

New bounds on the rate distortion function of certain non-Gaussian sources, with a proportional-weighted mean-square error (MSE) distortion measure, are given. The growth, g, of the rate distortion function, as a result of changing from a…

Information Theory · Computer Science 2007-07-13 Jacob Binia

Whenever inspected by humans, reconstructed signals should not be distinguished from real ones. Typically, such a high perceptual quality comes at the price of high reconstruction error, and vice versa. We study this distortion-perception…

Information Theory · Computer Science 2024-02-06 Dror Freirich , Nir Weinberger , Ron Meir

We consider a remote source coding problem subject to a {distortion function}. Contrary to the use of the classical separable distortion criterion, herein we consider the more general, $f$-separable distortion measure and study its…

Information Theory · Computer Science 2023-05-19 Photios A. Stavrou , Yanina Shkel , Marios Kountouris