• DocumentCode
    306410
  • Title

    Biologically motivated neural computing in early vision processing

  • Author

    Guan, L. ; Anderson, J.A. ; Sutton, J.P.

  • Author_Institution
    Dept. of Electr. Eng., Sydney Univ., NSW, Australia
  • Volume
    2
  • fYear
    1996
  • fDate
    14-17 Oct 1996
  • Firstpage
    1138
  • Abstract
    We introduce a network of networks (NoN) model to solve image processing problems in early vision. The method is motivated by the fact that natural image formation is a local process, and thus processing can be accomplished by a globally coordinated, local parallel processing structure, readily implemented by the hierarchical cluster architecture of the NoN model. The modeling is very powerful in that it achieves high quality adaptive processing, and virtually eliminates the computational difference between inhomogeneous and homogeneous conditions. Computer simulations show that this method is able to provide fast, quality image processing in early vision
  • Keywords
    computer vision; neural nets; parallel processing; quadratic programming; adaptive processing; early vision processing; hierarchical cluster architecture; image formation; image processing; image regularization; network of networks model; neural computing; parallel processing; quadratic programming; Biology computing; Computer vision; Degradation; Image processing; Image sensors; Neural networks; Optimization methods; Parallel processing; Pixel; Sensor arrays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1996., IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-3280-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.1996.571244
  • Filename
    571244