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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

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

Recent efforts in neural compression have focused on the rate-distortion-perception (RDP) tradeoff, where the perception constraint ensures the source and reconstruction distributions are close in terms of a statistical divergence.…

Information Theory · Computer Science 2025-05-21 Eric Lei , Hamed Hassani , Shirin Saeedi Bidokhti

End-to-end image transmission has recently become a crucial trend in intelligent wireless communications, driven by the increasing demand for high bandwidth efficiency. However, existing methods primarily optimize the trade-off between…

Image and Video Processing · Electrical Eng. & Systems 2024-08-27 Kailin Tan , Jincheng Dai , Zhenyu Liu , Sixian Wang , Xiaoqi Qin , Wenjun Xu , Kai Niu , Ping Zhang

The rate-distortion-perception (RDP) framework has attracted significant recent attention due to its application in neural compression. It is important to understand the underlying mechanism connecting procedures with common randomness and…

Information Theory · Computer Science 2024-06-28 Ruida Zhou , Chao Tian

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

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

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

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

A secrecy system with side information at the decoders is studied in the context of lossy source compression over a noiseless broadcast channel. The decoders have access to different side information sequences that are correlated with the…

Information Theory · Computer Science 2014-10-07 Eva C. Song , Paul Cuff , H. Vincent Poor

The fundamental limit of natural signal compression has traditionally been characterized by classical rate-distortion (RD) theory through the tradeoff between coding rate and reconstruction distortion, while the rate-distortion-perception…

Information Theory · Computer Science 2026-04-17 Zijian Liang , Kai Niu , Changshuo Wang , Jin Xu , Ping Zhang

Consider the problem where a statistician in a two-node system receives rate-limited information from a transmitter about marginal observations of a memoryless process generated from two possible distributions. Using its own observations,…

Information Theory · Computer Science 2017-03-02 Gil Katz , Pablo Piantanida , Mérouane Debbah

In image compression, with recent advances in generative modeling, the existence of a trade-off between the rate and the perceptual quality (realism) has been brought to light, where the realism is measured by the closeness of the output…

Information Theory · Computer Science 2024-04-02 Yassine Hamdi , Aaron B. Wagner , Deniz Gündüz

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 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

Rate-distortion optimization (RDO) of codecs, where distortion is quantified by the mean-square error, has been a standard practice in image/video compression over the years. RDO serves well for optimization of codec performance for…

Image and Video Processing · Electrical Eng. & Systems 2021-05-03 Ogun Kirmemis , A. Murat Tekalp

This paper applies Information Theoretic analysis to packet-based random multiple access communication systems. A new channel coding approach is proposed for coding within each data packet with built-in support for bursty traffic…

Information Theory · Computer Science 2016-11-17 Jie Luo , Anthony Ephremides

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

A rate-distortion-perception (RDP) tradeoff has recently been proposed by Blau and Michaeli and also Matsumoto. Focusing on the case of perfect realism, which coincides with the problem of distribution-preserving lossy compression studied…

Information Theory · Computer Science 2022-02-10 Aaron B. Wagner

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
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