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Real-time image compression using data-parallelism

  • P. Moravie
  • H. Essafi
  • C. Lambert-Nebout
  • J. -L. Basille
Posters: Extended Abstracts
Part of the Lecture Notes in Computer Science book series (LNCS, volume 966)

Abstract

The purpose of this paper is to present this new parallel image compression algorithm. We present implementation results on several parallel computers. We also examine load balancing and data mapping problems. We end by presenting a well-suited architecture for Real-Time image compression.

Keywords

Data-Parallelism Image Compression Wavelet Transform Vector Quantization Huffman Coding 

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References

  1. 1.
    M. Antonini, M. Barlaud, P. Mathieu, I. Daubechies. Image coding Using Wavelets Transform. IEEE Trans. on Image processing 1(4):205–220, 1992.Google Scholar
  2. 2.
    S. G. Mallat. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. on Pattern Analysis and Machine Inte lligence, 11(7): 674–693, 1989.Google Scholar
  3. 3.
    A. Gersho, R.M. Gray. Vector Quantization and Signal Compression. Kluwer Academic Publisher, Boston, 1992.Google Scholar
  4. 4.
    M. Nelson. The Data Compression book. Prentice Hall, Redwood Cityes, 1991.Google Scholar
  5. 5.
    M. J. Quinn. Designing Efficient Algorithms for Parallel Computers. McGraw-Hill, New York, NY, 1987.Google Scholar
  6. 6.
    R. W. Hockney and C. R. Jesshope. Parallel Computers: 2 Architecture, Programming, and Algorithms, 2nd Ed. IOP Publishing Ltd., Pennsylvania, 1988.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • P. Moravie
    • 1
  • H. Essafi
    • 1
  • C. Lambert-Nebout
    • 2
  • J. -L. Basille
    • 3
  1. 1.LETI (CEA - Technologies Avancées)Gif sur Yvette
  2. 2.Centre Spatial de ToulouseToulouse Cedex
  3. 3.ENSEEIHTToulouse Cedex

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