The Exponential Distribution in Rate Distortion Theory: The Case of Compression with Independent Encodings

Uri Erez, Jan Østergaard, Ram Zamir

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

In this paper, we consider the rate-distortion problem where a source X is encoded into k parallel descriptions Y1, . . . , Yk, such that the error signals X −Yi, i = 1, . . . , k, are mutually independent given X. We show that if X is one-sided exponentially distributed, the optimal decoder (estimator) under the one-sided absolute error criterion, is simply given by the maximum of the outputs Y1, . . . , Yk. We provide a closed-form expression for the rate and distortion for any k number of parallel descriptions and for any coding rate. We furthermore show that as the coding rate per description becomes asymptotically small, encoding into k parallel descriptions and using the maximum output as the source estimate, is rate-distortion optimal.
Original languageEnglish
Title of host publicationProceedings - DCC 2020 : Data Compression Conference
EditorsAli Bilgin, Michael W. Marcellin, Joan Serra-Sagrista, James A. Storer
Number of pages9
PublisherIEEE Signal Processing Society
Publication dateMar 2020
Pages323-331
Article number9105702
ISBN (Print)978-1-7281-6458-8
ISBN (Electronic)978-1-7281-6457-1
DOIs
Publication statusPublished - Mar 2020
Event2020 Data Compression Conference (DCC) - Snowbird, United States
Duration: 24 Mar 202027 Mar 2020

Conference

Conference2020 Data Compression Conference (DCC)
CountryUnited States
CitySnowbird
Period24/03/202027/03/2020
SeriesData Compression Conference
ISSN1068-0314

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