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Fundamental rate-distortion-perception (RDP) trade-offs arise in applications requiring maintained perceptual quality of reconstructed data, such as neural image compression. When compressed data is transmitted over public communication…

Information Theory · Computer Science 2026-04-23 Gustaf Åhlgren , Onur Günlü

Recent advances in machine learning-aided lossy compression are incorporating perceptual fidelity into the rate-distortion theory. In this paper, we study the rate-distortion-perception trade-off when the perceptual quality is measured by…

Information Theory · Computer Science 2023-05-23 Xueyan Niu , Deniz Gündüz , Bo Bai , Wei Han

The rate-distortion curve captures the fundamental tradeoff between compression length and resolution in lossy data compression. However, it conceals the underlying dynamics of optimal source encodings or test channels. We argue that these…

Information Theory · Computer Science 2023-07-03 Shlomi Agmon

Blau and Michaeli recently introduced a novel concept for inverse problems of signal processing, that is, the perception-distortion tradeoff. We introduce their tradeoff into the rate distortion theory of variable-length lossy source coding…

Information Theory · Computer Science 2019-02-12 Ryutaroh Matsumoto

In the successive refinement problem, a fixed-length sequence emitted from an information source is encoded into two codewords by two encoders in order to give two reconstructions of the sequence. One of two reconstructions is obtained by…

Information Theory · Computer Science 2018-12-26 Tetsunao Matsuta , Tomohiko Uyematsu

The problem of joint source-channel coding is considered for a stationary remote (noisy) Gaussian source and a Gaussian channel. The encoder and decoder are assumed to be causal and their combined operations are subject to a delay…

Information Theory · Computer Science 2012-03-29 Erik Johannesson , Anders Rantzer , Bo Bernhardsson , Andrey Ghulchak

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

This paper characterizes the second-order coding rates for lossy source coding with side information available at both the encoder and the decoder. We first provide non-asymptotic bounds for this problem and then specialize the…

Information Theory · Computer Science 2014-10-13 Sy-Quoc Le , Vincent Y. F. Tan , Mehul Motani

This paper considers the source coding problem with broadcast side information. The side information is sent to two receivers through a noisy broadcast channel. We provide an outer bound of the rate--distortion--bandwidth (RDB) quadruples…

Information Theory · Computer Science 2026-02-19 Yiqi Chen , Holger Boche , Marc Geitz

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

An important notion of common information between two random variables is due to Wyner. In this paper, we derive a lower bound on Wyner's common information for continuous random variables. The new bound improves on the only other general…

Information Theory · Computer Science 2021-02-17 Erixhen Sula , Michael Gastpar

This paper investigates a unification of distributed source coding, multiple description coding, and source coding with side information at decoders. The equivalence between the multiple-decoder extension of distributed source coding with…

Information Theory · Computer Science 2024-10-28 Jun Muramatsu

Explicit coding schemes are proposed to achieve the rate-distortion function of the Heegard-Berger problem using polar codes. Specifically, a nested polar code construction is employed to achieve the rate-distortion function for the…

Information Theory · Computer Science 2017-10-06 Jinwen Shi , Ling Liu , Deniz Gündüz , Cong Ling

A composite source, consisting of multiple subsources and a memoryless switch, outputs one symbol at a time from the subsource selected by the switch. If some data should be encoded more accurately than other data from an information…

Information Theory · Computer Science 2024-11-14 Jiakun Liu , H. Vincent Poor , Iickho Song , Wenyi Zhang

Consider a generalized multiterminal source coding system, where $\ell\choose m$ encoders, each observing a distinct size-$m$ subset of $\ell$ ($\ell\geq 2$) zero-mean unit-variance symmetrically correlated Gaussian sources with correlation…

Information Theory · Computer Science 2017-10-16 Jun Chen , Li Xie , Yameng Chang , Jia Wang , Yizhong Wang

We derive quantum counterparts of two key theorems of classical information theory, namely, the rate distortion theorem and the source-channel separation theorem. The rate-distortion theorem gives the ultimate limits on lossy data…

Quantum Physics · Physics 2012-12-21 Nilanjana Datta , Min-Hsiu Hsieh , Mark M. Wilde

In the first paper of this two part communication, we solved in a unified framework a variety of two terminal source coding problems with noncooperative encoders, thereby consolidating works of Shannon, Slepian-Wolf, Wyner,…

Information Theory · Computer Science 2007-07-13 Soumya Jana

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

Berger's paper `The Source Coding Game', IEEE Trans. Inform. Theory, 1971, considers the problem of finding the rate-distortion function for an adversarial source comprised of multiple known IID sources. The adversary, called the…

Information Theory · Computer Science 2007-07-13 Hari Palaiyanur , Cheng Chang , Anant Sahai

We consider the recovery of a continuous-time Wiener process from a quantized or lossy compressed version of its uniform samples under limited bitrate and sampling rate. We derive a closed form expression for the optimal tradeoff among…

Information Theory · Computer Science 2018-07-27 Alon Kipnis , Andrea J. Goldsmith , Yonina C. Eldar