• DocumentCode
    284867
  • Title

    Stochastic vector quantization of images

  • Author

    Torres, L. ; Arias, E.

  • Author_Institution
    Dept. of Signal Theory & Commun., Univ. Politechnica de Cataluna, Barcelona, Spain
  • Volume
    3
  • fYear
    1992
  • fDate
    23-26 Mar 1992
  • Firstpage
    385
  • Abstract
    The vector quantization scheme has proven to be very effective in image coding. One of the most important steps in the whole process is the design of the codebook. The codebook is generally designed using the Linde-Buzo-Gray algorithm, which is in essence a clustering algorithm that uses a large training set of empirical data that are statistically representative of the image to be quantized. The problem addressed is the stochastic generation of the codebook. The approach is to model the codebook according to some previous model defined for the image to be encoded and then to generate the training set according to the same model and not according to some specific data sequence. The model used is the well-known autoregressive model. Good visual results are shown in the range of 0.5-0.8 b/pixel
  • Keywords
    image coding; stochastic processes; vector quantisation; autoregressive model; image coding; stochastic codebook generation; training set; Algorithm design and analysis; Clustering algorithms; Code standards; Image coding; Pixel; Process design; Speech coding; Statistics; Stochastic processes; Vector quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-0532-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.1992.226220
  • Filename
    226220