Image coding using wavelet transforms and entropy-constrained trellis coded quantization

Parthasarathy Sriram, Michael W. Marcellin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multi-resolution approximations. Multi-resolution decomposition schemes have proven to be very effective for high-quality, low bit-rate image coding. In this work, we investigate the use of entropy-constrained trellis coded quantization for encoding the wavelet coefficients of both monochrome and color images. Excellent peak signal-to-noise ratios are obtained for encoding monochrome and color versions of the 512×512 `Lenna' Image. Comparisons with other results from the literature reveal that the proposed wavelet coder is quite competitive.

Original languageEnglish (US)
Title of host publicationImage and Multidimensional Signal Processing
PublisherPubl by IEEE
PagesV-554-V-557
ISBN (Print)0780309464
StatePublished - Jan 1 1993
EventIEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5) - Minneapolis, MN, USA
Duration: Apr 27 1993Apr 30 1993

Publication series

NameProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume5
ISSN (Print)0736-7791

Other

OtherIEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5)
CityMinneapolis, MN, USA
Period4/27/934/30/93

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Sriram, P., & Marcellin, M. W. (1993). Image coding using wavelet transforms and entropy-constrained trellis coded quantization. In Image and Multidimensional Signal Processing (pp. V-554-V-557). (Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing; Vol. 5). Publ by IEEE.