• DocumentCode
    1032890
  • Title

    Improved colour image vector quantisation by means of self-organising neural networks

  • Author

    Galli, I. ; Mecocci, A. ; Cappellini, Valeria

  • Author_Institution
    Dept. of Electron. Eng., Florence Univ.
  • Volume
    30
  • Issue
    4
  • fYear
    1994
  • fDate
    2/17/1994 12:00:00 AM
  • Firstpage
    333
  • Lastpage
    334
  • Abstract
    The problem of colour quantisation is important in many respects: colour monitors can usually display only a number of contemporary colours, and some images need to be represented in an approximate, even if satisfying, way. This is particularly true for the dissemination of images through communications networks and to information terminals. Moreover, colour quantised images can be stored in less space. The colour quantisation algorithm introduced by the authors is based on a set of neural cells structured in a self-organising two-dimensional map. The proposed technique provides high quality images and its neural architecture makes the algorithm flexible even if different kinds of source image are used. The hardware implementation is easy to realise and gives real-time performance
  • Keywords
    colour; image coding; self-organising feature maps; vector quantisation; SNR; colour image vector quantisation; colour monitors; communications networks; image dissemination; neural architecture; real-time performance; self-organising neural networks; self-organising two-dimensional map;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19940210
  • Filename
    267315