Iterative Algorithms Based on Decoupling of Deblurring and Denoising for Image Restoration

You Wei Wen, Michael K. Ng*, Wai Ki Ching

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

70 Citations (Scopus)
25 Downloads (Pure)


In this paper, we propose iterative algorithms for solving image restoration problems. The iterative algorithms are based on decoupling of deblurring and denoising steps in the restoration process. In the deblurring step, an efficient deblurring method using fast transforms can be employed. In the denoising step, effective methods such as the wavelet shrinkage denoising method or the total variation denoising method can be used. The main advantage of this proposal is that the resulting algorithms can be very efficient and can produce better restored images in visual quality and signal-to-noise ratio than those by the restoration methods using the combination of a data-fitting term and a regularization term. The convergence of the proposed algorithms is shown in the paper. Numerical examples are also given to demonstrate the effectiveness of these algorithms.

Original languageEnglish
Pages (from-to)2655-2674
Number of pages20
JournalSIAM Journal on Scientific Computing
Issue number5
Publication statusPublished - 6 Aug 2008

Scopus Subject Areas

  • Computational Mathematics
  • Applied Mathematics

User-Defined Keywords

  • Deblurring
  • Denoising
  • Image restoration
  • Iterative algorithms
  • Total variation
  • Wavelet


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