• DocumentCode
    2534379
  • Title

    Adaptive image sensing and enhancement using the adaptive cellular neural network Universal Machine

  • Author

    Brendel, Matyás ; Roska, Tantás

  • Author_Institution
    Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    93
  • Lastpage
    98
  • Abstract
    A simple but powerful active image equalization method is introduced via adaptive CNN-UM sensor-computers. The method can be used for the adaptive control of image sensing and for subsequent image enhancement. The algorithm uses intensity and contrast content as well. The method is completely executable on the adaptive cellular neural network Universal Machine (ACNN-UM) architecture. The adaptive extended cell is presented
  • Keywords
    adaptive control; cellular neural nets; image enhancement; active image equalization method; adaptive CNN-UM sensor-computers; adaptive cellular neural network Universal Machine; adaptive image sensing; Adaptive control; Adaptive equalizers; Adaptive systems; Cellular neural networks; Computer architecture; Computer networks; Concurrent computing; Histograms; Image enhancement; Turing machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications, 2000. (CNNA 2000). Proceedings of the 2000 6th IEEE International Workshop on
  • Conference_Location
    Catania
  • Print_ISBN
    0-7803-6344-2
  • Type

    conf

  • DOI
    10.1109/CNNA.2000.876827
  • Filename
    876827