• DocumentCode
    1904752
  • Title

    Image compression using topological maps and MLP

  • Author

    Burel, Gilles ; Catros, Jean-Yves

  • Author_Institution
    Thomson CSF, Cesson-Sevigne, France
  • fYear
    1993
  • fDate
    1993
  • Firstpage
    727
  • Abstract
    An image compression technique is proposed in which a multilayer perceptron (MLP) predictor takes advantage of the topological properties of the Kohonen algorithm. The Kohonen algorithm creates a code-book which is used for vector quantization of the source image. Then, an MLP is trained to predict references to code-book, allowing further compression. Even with difficult images, the result is a reduction of 15% to 20% of the bit rate compared with classical vector quantization techniques, for the same quality of decoded images
  • Keywords
    feedforward neural nets; image coding; image processing; topology; vector quantisation; Kohonen algorithm; code-book; image coding; image compression; image processing; multilayer perceptron; topological maps; vector quantization; Backpropagation; Bandwidth; Bit rate; Books; Decoding; Image coding; Image storage; Multilayer perceptrons; Transform coding; Vector quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993., IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    0-7803-0999-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1993.298645
  • Filename
    298645