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LLEC: An image coder with low-complexity and low-memory requirement

  • Harbin Institute of Technology
  • CAS - Institute of Computing Technology
  • City University of Hong Kong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A Low-complexity and Low-memory Entropy Coder (LLEC) for image compression is proposed in this paper. The two key elements in LLEC are zerotree coding and Golomb-Rice codes. Zerotree coding exploits the zerotree structure of transformed coefficients for higher compression efficiency. Golomb-Rice codes are used to code the remaining coefficients in a VLC/VLI manner for low complexity and low memory. The experimental results show that the compression efficiency of DCT- and DWT-based LLEC outperforms baseline JPEG and EZW at the given bit rates, respectively. When compared with SPIHT, LLEC is inferior by 0.3 dB on average for the tested images but superior in terms of computational complexity and memory requirement. In addition, LLEC has other desirable features such as parallel processing support, ROI (Region Of Interest) coding and as a universal entropy coder for DCT and DWT.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings
EditorsHeung-Yeung Shum, Mark Liao, Shih-Fu Chang
PublisherSpringer Verlag
Pages957-962
Number of pages6
ISBN (Print)3540426809, 9783540426806
DOIs
StatePublished - 2001
Event2nd IEEE Pacific-Rim Conference on Multimedia, IEEE-PCM 2001 - Beijing, China
Duration: 24 Oct 200126 Oct 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2195
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd IEEE Pacific-Rim Conference on Multimedia, IEEE-PCM 2001
Country/TerritoryChina
CityBeijing
Period24/10/0126/10/01

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