• DocumentCode
    294839
  • Title

    Permutative vector quantization-application to image compression

  • Author

    Skowronski, J. ; Dologlou, I.

  • Author_Institution
    Lab. des Signaux et Syst., CNRS, Gif-sur-Yvette, France
  • Volume
    4
  • fYear
    1995
  • fDate
    9-12 May 1995
  • Firstpage
    2587
  • Abstract
    The paper describes the permutative vector quantization (PVQ) scheme as a special case of a more general structurally constrained vector quantization concept. This concept makes it possible to increase the vector dimensions beyond the technical bounds of conventional VQ and to exploit, by means of this, the inter-pixel correlations in large image blocks. Furthermore, a codebook design algorithm adapted to permutative VQ is proposed and it is shown experimentally that the coding performance of conventional VQ can be improved using the present scheme
  • Keywords
    correlation methods; image coding; vector quantisation; codebook design algorithm; image compression; inter-pixel correlations; permutative vector quantization; vector dimensions; Algorithm design and analysis; Books; Clustering algorithms; Data compression; Image coding; Nearest neighbor searches; Neural networks; Rate distortion theory; Statistics; Vector quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
  • Conference_Location
    Detroit, MI
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-2431-5
  • Type

    conf

  • DOI
    10.1109/ICASSP.1995.480078
  • Filename
    480078