• DocumentCode
    2153183
  • Title

    Defocused Image Restoration Using RBF Network and Iterative Wiener Filter in Wavelet Domain

  • Author

    Su, Li-yun ; Li, Feng-lan ; Xu, Feng ; Liu, Yu-ran

  • Volume
    3
  • fYear
    2008
  • fDate
    27-30 May 2008
  • Firstpage
    311
  • Lastpage
    315
  • Abstract
    A novel semi-blind defocused image deconvolution technique is proposed, which is based on RBF neural network and iterative Wiener filtering. In this technique, firstly a RBF neural network is trained in wavelet domain to estimate defocus parameter. After obtaining the point spread function (PSF) parameter, iterative Wiener filter is adopted to complete the restoration. We experimentally illustrate its performance on simulated data. Results show that the proposed PSF parameter estimation technique is effective and has high performance.
  • Keywords
    Additive noise; Degradation; Image restoration; Mathematics; Neural networks; Optical noise; Parameter estimation; Radial basis function networks; Wavelet domain; Wiener filter; Defocused Image Deconvolution; Iterative Wiener Filtering; RBF Neural Network; Wavelet Transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing, 2008. CISP '08. Congress on
  • Conference_Location
    Sanya, China
  • Print_ISBN
    978-0-7695-3119-9
  • Type

    conf

  • DOI
    10.1109/CISP.2008.260
  • Filename
    4566496