Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published September 2001 | public
Journal Article Open

Universal multiresolution source codes

Abstract

A multiresolution source code is a single code giving an embedded source description that can be read at a variety of rates and thereby yields reproductions at a variety of resolutions. The resolution of a source reproduction here refers to the accuracy with which it approximates the original source. Thus, a reproduction with low distortion is a "high-resolution" reproduction while a reproduction with high distortion is a "low-resolution" reproduction. This paper treats the generalization of universal lossy source coding from single-resolution source codes to multiresolution source codes. Results described in this work include new definitions for weakly minimax universal, strongly minimax universal, and weighted universal sequences of fixed- and variable-rate multiresolution source codes that extend the corresponding notions from lossless coding and (single-resolution) quantization to multiresolution quantizers. A variety of universal multiresolution source coding results follow, including necessary and sufficient conditions for the existence of universal multiresolution codes, rate of convergence bounds for universal multiresolution coding performance to the theoretical bound, and a new multiresolution approach to two-stage universal source coding.

Additional Information

©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Manuscript received April 13, 1999; revised June 22, 2000. This work was supported in part by NSF CAREER Award MIP-9501977, NSF Award CCR-9909026, under a grant from the Charles Lee Powell Foundation, and a grant from Caltech's Lee Center for Advanced Networks. The material in this paper was presented in part at the 1999 IEEE Information Theory Workshop (DECI), Santa Fe, NM, February 1999. Communicated by N. Merhav, Associate Editor for Source Coding.

Files

EFFieeetit01.pdf
Files (608.7 kB)
Name Size Download all
md5:4a32f9a71dc9ac065e912225f6ee610f
608.7 kB Preview Download

Additional details

Created:
August 21, 2023
Modified:
October 13, 2023