• DocumentCode
    2658046
  • Title

    Blur identification and image restoration using a multilayer neural network

  • Author

    Cho, Chao-Ming ; Don, Hon-Son

  • Author_Institution
    Dept. of Electr. Eng., State Univ. of New York, Stony Brook, NY, USA
  • fYear
    1991
  • fDate
    18-21 Nov 1991
  • Firstpage
    2558
  • Abstract
    A neural network model combining an adaptive heteroassociative network and an adaptive autoassociative network with a random Gaussian process is proposed to identify the noncausal blur function and to restore the blurred image at the same time. The noisy blurred images are modeled as continuous associative networks, where the autoassociative part determines the image model coefficients and the heteroassociative part determines the blur function of the system. The estimation and restoration are implemented by using an iterative steepest descent algorithm to minimize the error functions of the networks. Experiment results demonstrate that effective identification and restoration can be performed
  • Keywords
    adaptive systems; content-addressable storage; iterative methods; neural nets; pattern recognition; picture processing; random processes; adaptive autoassociative network; adaptive heteroassociative network; blur identification; continuous associative networks; error function minimization; image restoration; iterative steepest descent algorithm; multilayer neural network; noncausal blur function; random Gaussian process; Adaptive systems; Autoregressive processes; Chaos; Degradation; Gaussian processes; Image restoration; Iterative algorithms; Multi-layer neural network; Neural networks; Parameter estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991. 1991 IEEE International Joint Conference on
  • Print_ISBN
    0-7803-0227-3
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.170774
  • Filename
    170774