English
Related papers

Related papers: Rate-Distortion-Perception Theory for the Quadrati…

200 papers

The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of squared error distortion measure. An explicit expression is obtained when both source and…

Information Theory · Computer Science 2024-03-25 Li Xie , Liangyan Li , Jun Chen , Zhongshan Zhang

This paper investigates the best known bounds on the quadratic Gaussian distortion-rate-perception function with limited common randomness for the Kullback-Leibler divergence-based perception measure, as well as their counterparts for the…

Information Theory · Computer Science 2024-09-05 Li Xie , Liangyan Li , Jun Chen , Lei Yu , Zhongshan Zhang

The lower the distortion of an estimator, the more the distribution of its outputs generally deviates from the distribution of the signals it attempts to estimate. This phenomenon, known as the perception-distortion tradeoff, has captured…

Image and Video Processing · Electrical Eng. & Systems 2021-07-07 Dror Freirich , Tomer Michaeli , Ron Meir

Wasserstein distortion is a one-parameter family of distortion measures that was recently proposed to unify fidelity and realism constraints. After establishing continuity results for Wasserstein in the extreme cases of pure fidelity and…

Information Theory · Computer Science 2024-01-31 Yang Qiu , Aaron B. Wagner

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

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

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

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

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

Information Theory · Computer Science 2023-05-23 Yassine Hamdi , Deniz Gündüz

We introduce a distortion measure for images, Wasserstein distortion, that simultaneously generalizes pixel-level fidelity on the one hand and realism or perceptual quality on the other. We show how Wasserstein distortion reduces to a pure…

Information Theory · Computer Science 2024-04-01 Yang Qiu , Aaron B. Wagner , Johannes Ballé , Lucas Theis

Rate-distortion-perception theory generalizes Shannon's rate-distortion theory by introducing a constraint on the perceptual quality of the output. The perception constraint complements the conventional distortion constraint and aims to…

Information Theory · Computer Science 2022-04-14 Jun Chen , Lei Yu , Jia Wang , Wuxian Shi , Yiqun Ge , Wen Tong

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

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

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

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

A new source model, which consists of an intrinsic state part and an extrinsic observation part, is proposed and its information-theoretic characterization, namely its rate-distortion function, is defined and analyzed. Such a source model…

Information Theory · Computer Science 2022-06-02 Jiakun Liu , Shuo Shao , Wenyi Zhang , H. Vincent Poor

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 lossy source coding in information…

Information Theory · Computer Science 2018-11-01 Ryutaroh Matsumoto

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 lossy compression, Wang et al. [1] recently introduced the rate-distortion-perception-classification function, which supports multi-task learning by jointly optimizing perceptual quality, classification accuracy, and reconstruction…

Information Theory · Computer Science 2025-04-23 Nam Nguyen , Thuan Nguyen , Thinh Nguyen , Bella Bose

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
‹ Prev 1 2 3 10 Next ›