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In this paper, we study the computation of the rate-distortion-perception function (RDPF) for a multivariate Gaussian source under mean squared error (MSE) distortion and, respectively, Kullback-Leibler divergence, geometric Jensen-Shannon…

Information Theory · Computer Science 2023-11-16 Giuseppe Serra , Photios A. Stavrou , Marios Kountouris

In this paper, we investigate the rate-distortion-perception function (RDPF) of a source modeled by a Gaussian Process (GP) on a measure space $\Omega$ under mean squared error (MSE) distortion and squared Wasserstein-2 perception metrics.…

Information Theory · Computer Science 2025-01-14 Giuseppe Serra , Photios A. Stavrou , Marios Kountouris

This paper studies the rate-distortion-perception (RDP) tradeoff for a Gaussian vector source coding problem where the goal is to compress the multi-component source subject to distortion and perception constraints. Specifically, the RDP…

Information Theory · Computer Science 2025-03-18 Jingjing Qian , Sadaf Salehkalaibar , Jun Chen , Ashish Khisti , Wei Yu , Wuxian Shi , Yiqun Ge , Wen Tong

In this paper, we study the computation of the rate-distortion-perception function (RDPF) for discrete memoryless sources subject to a single-letter average distortion constraint and a perception constraint that belongs to the family of…

Information Theory · Computer Science 2023-05-09 Giuseppe Serra , Photios A. Stavrou , Marios Kountouris

In this paper, we consider a distributed remote source coding problem, where a sequence of observations of source vectors is available at the encoder. The problem is to specify the optimal rate for encoding the observations subject to a…

Information Theory · Computer Science 2014-06-05 Adel Zahedi , Jan Ostergaard , Soren Holdt Jensen , Patrick Naylor , Soren Bech

The rate-distortion-perception function (RDPF; Blau and Michaeli, 2019) has emerged as a useful tool for thinking about realism and distortion of reconstructions in lossy compression. Unlike the rate-distortion function, however, it is…

Information Theory · Computer Science 2021-04-29 Lucas Theis , Aaron B. Wagner

The rate-distortion function (RDF) has long been an information-theoretic benchmark for data compression. As its natural extension, the indirect rate-distortion function (iRDF) corresponds to the scenario where the encoder can only access…

Information Theory · Computer Science 2025-03-11 Zichao Yu , Qiang Sun , Wenyi Zhang

In this paper, we consider the rate-distortion-perception (RDP) trade-off for the lossy compression of a Bernoulli vector source, which is a finite collection of independent binary random variables. The RDP function quantifies in a way the…

Information Theory · Computer Science 2025-01-22 Praneeth Kumar Vippathalla , Mihai-Alin Badiu , Justin P. Coon

We present a new method to estimate the rate-distortion-perception function in the perfect realism regime (PR-RDPF), for multivariate continuous sources subject to a single-letter average distortion constraint. The proposed approach is not…

Information Theory · Computer Science 2024-01-31 Giuseppe Serra , Photios A. Stavrou , Marios Kountouris

In this paper we analyze the joint rate distortion function (RDF), for a tuple of correlated sources taking values in abstract alphabet spaces (i.e., continuous) subject to two individual distortion criteria. First, we derive structural…

Information Theory · Computer Science 2021-05-11 Evagoras Stylianou , Charalambos D. Charalambous , Themistoklis Charalambous

This paper studies the rate-distortion-perception (RDP) tradeoff for a memoryless source model in the asymptotic limit of large block-lengths. The perception measure is based on a divergence between the distributions of the source and…

Information Theory · Computer Science 2025-04-29 Sadaf Salehkalaibar , Jun Chen , Ashish Khisti , Wei Yu

We extend the Rate-Distortion-Perception (RDP) framework to the R\'enyi information-theoretic regime, utilizing Sibson's $\alpha$-mutual information to characterize the fundamental limits under distortion and perception constraints. For…

Information Theory · Computer Science 2026-05-12 Jiahui Wei , Marios Kountouris

We improve the existing achievable rate regions for causal and for zero-delay source coding of stationary Gaussian sources under an average mean squared error (MSE) distortion measure. To begin with, we find a closed-form expression for the…

Information Theory · Computer Science 2011-05-03 Milan S. Derpich , Jan Østergaard

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

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 this paper, we analyze the indirect source coding problem with side information at both the encoder and decoder, as well as only at the decoder. We first derive structural properties of the two rate distortion functions (RDFs) for…

Information Theory · Computer Science 2024-10-14 Evagoras Stylianou , Michail Gkagkos , Charalambos D. Charalambous

We deal with zero-delay source coding of a vector-valued Gauss-Markov source subject to a mean-squared error (MSE) fidelity criterion characterized by the operational zero-delay vector-valued Gaussian rate distortion function (RDF). We…

Information Theory · Computer Science 2018-10-02 Photios A. Stavrou , Jan Ostergaard , Charalambos D. Charalambous

In this paper the relation between nonanticipative rate distortion function (RDF) and Bayesian filtering theory is further investigated on general Polish spaces. The relation is established via an optimization on the space of conditional…

Information Theory · Computer Science 2014-01-21 Photios A. Stavrou , Charalambos D. Charalambous

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

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
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