Surrogate functional based subspace correction methods for image processing

M. Hintermüller, A. Langer

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

1 Citation (Scopus)

Abstract

In this paper we present subspace correction methods for non-smooth and non-additive energies which are guaranteed to converge. Moreover, we are able to provide an estimate of the distance between the outcome of the subspace correction method and the global minimizer of the non-smooth and non-additive objective. With the help of this estimate we can finally show in our numerical experiments that the proposed method even converges to a true global minimizer.
Original languageEnglish
Title of host publicationDomain Decomposition Methods in Science and Engineering XXI
EditorsJocelyne Erhel, Martin J. Gander, Laurence Halpern, Géraldine Pichot, Taoufik Sassi, Olof Widlund
PublisherSpringer, Cham
Pages829-837
Number of pages9
ISBN (Electronic)978-3-319-05789-7
ISBN (Print)978-3-319-05788-0
DOIs
Publication statusPublished - 21 Apr 2014
Externally publishedYes
Event 21st international conference on domain decomposition methods in science and engineering - Rennes, France
Duration: 25 Jun 201229 Jun 2012

Conference

Conference 21st international conference on domain decomposition methods in science and engineering
CountryFrance
City Rennes
Period25/06/1229/06/12

Fingerprint Dive into the research topics of 'Surrogate functional based subspace correction methods for image processing'. Together they form a unique fingerprint.

  • Cite this

    Hintermüller, M., & Langer, A. (2014). Surrogate functional based subspace correction methods for image processing. In J. Erhel, M. J. Gander, L. Halpern, G. Pichot, T. Sassi, & O. Widlund (Eds.), Domain Decomposition Methods in Science and Engineering XXI (pp. 829-837). Springer, Cham . https://doi.org/10.1007/978-3-319-05789-7__80