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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 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

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

Shannon's rate-distortion theory treats source symbols as unstructured labels. When the source is a knowledge base equipped with a logical proof system, a natural fidelity criterion is closure fidelity: a reconstruction is acceptable if it…

Information Theory · Computer Science 2026-04-14 Jianfeng Xu

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

We consider the semantic rate-distortion problem motivated by task-oriented video compression. The semantic information corresponding to the task, which is not observable to the encoder, shows impacts on the observations through a joint…

Information Theory · Computer Science 2022-08-15 Tao Guo , Yizhu Wang , Jie Han , Huihui Wu , Bo Bai , Wei Han

In lossy compression, the classical tradeoff between compression rate and reconstruction distortion has traditionally guided algorithm design. However, Blau and Michaeli [5] introduced a generalized framework, known as the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Nam Nguyen

This paper studies the fundamental limit of semantic communications over the discrete memoryless channel. We consider the scenario to send a semantic source consisting of an observation state and its corresponding semantic state, both of…

Information Theory · Computer Science 2024-01-03 Dongxu Li , Jianhao Huang , Chuan Huang , Xiaoqi Qin , Han Zhang , Ping Zhang

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

Information Theory · Computer Science 2025-07-22 Yassine Hamdi , Aaron B. Wagner , Deniz Gündüz

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

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

Consider the problem of estimating a latent signal from a lossy compressed version of the data when the compressor is agnostic to the relation between the signal and the data. This situation arises in a host of modern applications when data…

Information Theory · Computer Science 2021-01-12 Alon Kipnis , Stefano Rini , Andrea J. Goldsmith

We propose conditional perceptual quality, an extension of the perceptual quality defined in \citet{blau2018perception}, by conditioning it on user defined information. Specifically, we extend the original perceptual quality…

Image and Video Processing · Electrical Eng. & Systems 2023-08-17 Tongda Xu , Qian Zhang , Yanghao Li , Dailan He , Zhe Wang , Yuanyuan Wang , Hongwei Qin , Yan Wang , Jingjing Liu , Ya-Qin Zhang

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

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

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

Perception-aware lossy source coding has attracted significant recent interest. It augments the classical distortion criterion with an explicit perception constraint, thereby enabling more refined control over fidelity and perceptual…

Information Theory · Computer Science 2026-04-22 Ali Hussein , Jun Chen , Chao Tian , S. Sandeep Pradhan

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

Generalization to novel visual conditions remains a central challenge for both human and machine vision, yet standard robustness metrics offer limited insight into how systems trade accuracy for robustness. We introduce a…

Machine Learning · Computer Science 2026-03-03 Leyla Roksan Caglar , Pedro A. M. Mediano , Baihan Lin

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