• DocumentCode
    3209452
  • Title

    Wavelet Image Restoration and Regularization Parameters Selection

  • Author

    Qu, Leming

  • Author_Institution
    Dept. of Math., Boise State Univ., Boise, ID, USA
  • fYear
    2009
  • fDate
    17-19 Dec. 2009
  • Firstpage
    241
  • Lastpage
    247
  • Abstract
    For the restoration of an image based on its noisy distorted observations, we propose wavelet domain restoration by scale-dependent ¿1 penalized regularization method (WaveRSL1). The data adaptive choice of the regularization parameters is based on the Akaike Information Criterion (AIC) and the degrees of freedom (df) is estimated by the number of nonzero elements in the solution. Experiments on some commonly used testing images illustrate that the proposed method possesses good empirical properties.
  • Keywords
    image restoration; wavelet transforms; Akaike information criterion; image deblurring; regularization parameters selection; scale-dependent ¿1 penalized regularization method; wavelet image restoration; Bayesian methods; Computer science; Fast Fourier transforms; Image restoration; Inverse problems; Mathematics; Noise reduction; Testing; Wavelet domain; Wavelet transforms; AIC; Lasso; Wavelet; image restoration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Frontier of Computer Science and Technology, 2009. FCST '09. Fourth International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3932-4
  • Electronic_ISBN
    978-1-4244-5467-9
  • Type

    conf

  • DOI
    10.1109/FCST.2009.18
  • Filename
    5392910