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Multiresolution vector quantization

Effros, Michelle and Dugatkin, Diego (2004) Multiresolution vector quantization. IEEE Transactions on Information Theory, 50 (12). pp. 3130-3145. ISSN 0018-9448. doi:10.1109/TIT.2004.838381.

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Multiresolution source codes are data compression algorithms yielding embedded source descriptions. The decoder of a multiresolution code can build a source reproduction by decoding the embedded bit stream in part or in whole. All decoding procedures start at the beginning of the binary source description and decode some fraction of that string. Decoding a small portion of the binary string gives a low-resolution reproduction; decoding more yields a higher resolution reproduction; and so on. Multiresolution vector quantizers are block multiresolution source codes. This paper introduces algorithms for designing fixed- and variable-rate multiresolution vector quantizers. Experiments on synthetic data demonstrate performance close to the theoretical performance limit. Experiments on natural images demonstrate performance improvements of up to 8 dB over tree-structured vector quantizers. Some of the lessons learned through multiresolution vector quantizer design lend insight into the design of more sophisticated multiresolution codes.

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Additional Information:“©2004 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 October 20, 2000; revised November 22, 2002. Posted online: 2004-11-30. The material in this paper was presented in part at the 1998 Data Compression Conference and the 1998 Asilomar Conference on Signals and Systems. This material is based on work supported in part by the National Science Foundation CAREER Award MIP-9501977, a grant from the Charles Lee Powell Foundation, donations through the Intel 2000 Program, and the Oringer Fellowship. The authors wish to thank the anonymous reviewers and the Associate Editor for suggestions that improved the quality of this paper. In particular, the generalization from greedy search (N = 1) to N-path search (N >= 1)in the LMRVQ was proposed by a reviewer.
Subject Keywords:Embedded source code design, fixed rate, multiuser, network, progressive transmission, successive refinement, variable rate, source code design, source coding theory, network information theory
Issue or Number:12
Record Number:CaltechAUTHORS:EFFieeetit04a
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:1331
Deposited By: Archive Administrator
Deposited On:10 Jan 2006
Last Modified:08 Nov 2021 19:09

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