A fast total variation minimization method for image restoration

Yumei Huang*, Kwok Po NG, You Wei Wen

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

206 Citations (Scopus)


In this paper, we study a fast total variation minimization method for image restoration. In the proposed method, we use the modified total variation minimization scheme to denoise the deblurred image. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show that the quality of restored images by the proposed method is competitive with those restored by the existing total variation restoration methods. We show the convergence of the alternating minimization algorithm and demonstrate that thealgorithm is very efficient.

Original languageEnglish
Pages (from-to)774-795
Number of pages22
JournalMultiscale Modeling and Simulation
Issue number2
Publication statusPublished - 2008

Scopus Subject Areas

  • Chemistry(all)
  • Modelling and Simulation
  • Ecological Modelling
  • Physics and Astronomy(all)
  • Computer Science Applications

User-Defined Keywords

  • Deblurring
  • Denoising
  • Image restoration
  • Total variation


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