• DocumentCode
    2561464
  • Title

    Complex wavelet based image deconvolution

  • Author

    Li, Min ; Wu, Xiao-Hong ; Jiang, Qiang ; Zhang, Xiao-ying

  • Author_Institution
    Dept. of Phys. & Electr. Inf., Leshan Normal Univ., Leshan
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    2357
  • Lastpage
    2362
  • Abstract
    For image deconvolution, there are more methods, such as the CLEAN algorithm, maximum entropy deconvolution and iterative reconstruction. When the image contains sharp edges, these methods are less appropriate. Recently, we attempt to improve the performance near edges. In this paper we advance a new method PRECGDT-CWT, using the standard DT-CWT(Dual Tree- Complex Wavelet Transform) filters of the (13-19) taps near orthogonal filters at level 1 together with the 14-tap Q-shift filters at levels not less than 2.We chose ten iterations of the PRECG(the Conjugate Gradient algorithm used with the Preconditioned system) search direction starting from a WaRD estimate. We also compare the results with alternative deconvolution algorithms. The method of PRECGDT-CWT performs better than all the other methods tested and the published results on similar deconvolution experiments.
  • Keywords
    conjugate gradient methods; deconvolution; image processing; maximum entropy methods; wavelet transforms; 14-tap Q-shift filters; CLEAN algorithm; PRECGDT-CWT; WaRD estimate; complex wavelet based image deconvolution; conjugate gradient algorithm; dual tree complex wavelet transform; iterative reconstruction; maximum entropy deconvolution; preconditioned system; Bayesian methods; Deconvolution; Delay; Filters; Image reconstruction; Inference algorithms; Iterative algorithms; Iterative methods; Tree data structures; Wavelet transforms; Image deconvolution; Q-shift dual tree; complex wavelet transform; conjugate gradient algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4597746
  • Filename
    4597746