Non-Overlapping Domain Decomposition Methods For Dual Total Variation Based Image Denoising

M. Hintermüller, A. Langer

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


In this paper non-overlapping domain decomposition methods for the pre-dual total variation minimization problem are introduced. Both parallel and sequential approaches are proposed for these methods for which convergence to a minimizer of the original problem is established. The associated subproblems are solved by a semi-smooth Newton method. Several numerical experiments are presented, which show the successful application of the sequential and parallel algorithm for image denoising.
Original languageEnglish
Pages (from-to)456–481
Number of pages26
JournalJournal of Scientific Computing
Early online date7 May 2014
Publication statusPublished - Feb 2015
Externally publishedYes


  • Domain decomposition
  • Subspace correction
  • Total bounded variation
  • Pre-dual
  • Convex optimization
  • Convergence analysis
  • Image reconstruction


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