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Efficient zerotree-based image compression with directionlets

  • University of Valencia
    ,
  • University of California at Berkeley
    ,
  • Swiss Federal Institute of Technology Lausanne
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Open access

Abstract

Directionlets are built as basis functions of critically sampled perfect-reconstruction transforms with directional vanishing moments (DVMs) imposed along different directions. Here, we combine the directionlets with the spacefrequency quantization (SFQ) image compression method, originally based on the standard two-dimensional (2-D) wavelet transform (WT). We show that our new compression method outperforms the standard SFQ as well as the stateof-the-art image compression methods, such as SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of computational complexity remains the same, as compared to the complexity of the standard SFQ algorithm.

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 807-811 (5 pages)

Publication milestones

  • Published - 01/01/2007

Publication status

Published - 01/01/2007

Publisher

European Signal Processing Conference, EUSIPCO, Belgium

Publication series

  • Publication series name: European Signal Processing Conference
    ISSN (Print): 2219-5491

ISBN (Print)

9788392134022

ISBN (Electronic)

9781617388767

Publication IDs

  • handle.net: 10547/292618
  • Scopus: 84863767841

Host publication title

15th European Signal Processing Conference, EUSIPCO 2007 - Proceedings

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