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Domain Decomposition for Non-smooth (in Particular TV) Minimization

In: Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

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  • Andreas Langer

    (Lund University, Centre for Mathematical Sciences)

Abstract

Domain decomposition is one of the most efficient techniques to derive efficient methods for large-scale problems. In this chapter such decomposition methods for the minimization of the total variation are discussed. We differ between approaches which directly tackle the (primal) total variation minimization and approaches which deal with their predual formulation. Thereby we mainly concentrate on the presentation of domain decomposition methods which guarantee to converge to a solution of the global problem.

Suggested Citation

  • Andreas Langer, 2023. "Domain Decomposition for Non-smooth (in Particular TV) Minimization," Springer Books, in: Ke Chen & Carola-Bibiane Schönlieb & Xue-Cheng Tai & Laurent Younes (ed.), Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, chapter 11, pages 379-425, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-98661-2_104
    DOI: 10.1007/978-3-030-98661-2_104
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