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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

The problem of estimating the information rate distortion perception function (RDPF), which is a relevant information-theoretic quantity in goal-oriented lossy compression and semantic information reconstruction, is investigated here.…

Information Theory · Computer Science 2025-09-25 Martha V. Sourla , 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

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

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

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 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

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 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

A general expression for the distortion rate function (DRF) of cyclostationary Gaussian processes in terms of their spectral properties is derived. This expression can be seen as the result of orthogonalization over the different components…

Information Theory · Computer Science 2016-08-11 Alon Kipnis , Andrea J. Goldsmith , Yonina C. Eldar

The information rate-distortion-perception (RDP) function characterizes the three-way trade-off between description rate, average distortion, and perceptual quality measured by discrepancy between probability distributions and has been…

Information Theory · Computer Science 2024-10-31 Chunhui Chen , Xueyan Niu , Wenhao Ye , Hao Wu , Bo Bai

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

The nascent field of Rate-Distortion-Perception (RDP) theory is seeing a surge of research interest due to the application of machine learning techniques in the area of lossy compression. The information RDP function characterizes the…

Information Theory · Computer Science 2023-05-01 Chunhui Chen , Xueyan Niu , Wenhao Ye , Shitong Wu , Bo Bai , Weichao Chen , Sian-Jheng Lin

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

We deal with zero-delay source coding of a vector Gaussian autoregressive (AR) source subject to an average mean squared error (MSE) fidelity criterion. Toward this end, we consider the nonanticipative rate distortion function (NRDF) which…

Information Theory · Computer Science 2017-08-22 Photios A. Stavrou , Jan Ostergaard , Charalambos D. Charalambous , Milan Derpich

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

We prove achievability of the recently characterized quadratic Gaussian rate-distortion function (RDF) subject to the constraint that the distortion is uncorrelated to the source. This result is based on shaped dithered lattice quantization…

Information Theory · Computer Science 2008-07-24 Milan S. Derpich , Jan Ostergaard , Daniel E. Quevedo

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

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 study the rate-distortion function (RDF) for the lossy compression of discrete-time (DT) wide-sense almost cyclostationary (WSACS) Gaussian processes with memory, arising from sampling continuous-time (CT) wide-sense cyclostationary…

Information Theory · Computer Science 2025-07-02 Zikun Tan , Ron Dabora , H. Vincent Poor
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