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

Hintermüller, Michael and Langer, Andreas LU (2014) In Journal of Scientific Computing 62(2). p.456-481
Abstract

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.

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author
and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Convergence analysis, Convex optimization, Domain decomposition, Image reconstruction, Pre-dual, Subspace correction, Total bounded variation
in
Journal of Scientific Computing
volume
62
issue
2
pages
26 pages
publisher
Springer
external identifiers
  • scopus:84921066590
ISSN
0885-7474
DOI
10.1007/s10915-014-9863-8
language
English
LU publication?
no
additional info
Publisher Copyright: © 2014, Springer Science+Business Media New York. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
id
fcf0f2d6-361b-4bd8-9380-b73fb76225f9
date added to LUP
2021-03-15 22:32:13
date last changed
2022-02-23 15:31:46
@article{fcf0f2d6-361b-4bd8-9380-b73fb76225f9,
  abstract     = {{<p>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.</p>}},
  author       = {{Hintermüller, Michael and Langer, Andreas}},
  issn         = {{0885-7474}},
  keywords     = {{Convergence analysis; Convex optimization; Domain decomposition; Image reconstruction; Pre-dual; Subspace correction; Total bounded variation}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{456--481}},
  publisher    = {{Springer}},
  series       = {{Journal of Scientific Computing}},
  title        = {{Non-Overlapping Domain Decomposition Methods For Dual Total Variation Based Image Denoising}},
  url          = {{http://dx.doi.org/10.1007/s10915-014-9863-8}},
  doi          = {{10.1007/s10915-014-9863-8}},
  volume       = {{62}},
  year         = {{2014}},
}