• DocumentCode
    2905904
  • Title

    Vector quantization and progressive image transmission using Kohonen self-organizing feature map

  • Author

    Gong, Wei ; Rao, K.R. ; Manry, Michael T.

  • Author_Institution
    Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
  • fYear
    1991
  • fDate
    4-6 Nov 1991
  • Firstpage
    477
  • Abstract
    Vector quantization is implemented using a modified Kohonen self-organizing feature map algorithm, called KVQ. To alleviate edge distortion a classification technique is applied to vector quantization. The classification technique is based on edge detection, since the human visual system is more sensitive to edges. A simple spatial domain progressive image transmission is presented, which uses separating mean KVQ. In simulation results, very good intermediate images were obtained at reasonable bit rates
  • Keywords
    data compression; encoding; neural nets; picture processing; self-adjusting systems; visual communication; KVQ; Kohonen self-organizing feature map; algorithm; classification; edge detection; neural nets; spatial domain progressive image transmission; vector quantisation; Bit rate; Clustering algorithms; Euclidean distance; Humans; Image coding; Image communication; Image edge detection; Rate-distortion; Vector quantization; Visual system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA
  • ISSN
    1058-6393
  • Print_ISBN
    0-8186-2470-1
  • Type

    conf

  • DOI
    10.1109/ACSSC.1991.186495
  • Filename
    186495