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The Total Variation-Wasserstein Problem

Chambolle, Antonin; Duval, Vincent; Machado, Joao Miguel (2023), The Total Variation-Wasserstein Problem, in Nielsen, F., Barbaresco, F. (eds), Geometric Science of Information. GSI 2023. Lecture Notes in Computer Science, vol 14071, Springer International Publishing : Berlin Heidelberg, p. 610-619. 10.1007/978-3-031-38271-0_61

Type
Communication / Conférence
External document link
https://hal.science/hal-04113284
Date
2023
Conference title
Geometric Science of Information. GSI 2023
Conference date
2023-08
Conference city
Saint Malo
Conference country
France
Book title
Geometric Science of Information. GSI 2023. Lecture Notes in Computer Science, vol 14071
Book author
Nielsen, F., Barbaresco, F. (eds)
Publisher
Springer International Publishing
Published in
Berlin Heidelberg
ISBN
978-3-031-38270-3
Number of pages
624
Pages
610-619
Publication identifier
Metadata
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Author(s)
Chambolle, Antonin cc
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Duval, Vincent cc
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Machado, Joao Miguel
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Abstract (EN)
In this work we analyze the Total Variation-Wasserstein minimization problem. We propose an alternative form of deriving optimality conditions from the approach of [8], and as result obtain further regularity for the quantities involved. In the sequel we propose an algorithm to solve this problem alongside two numerical experiments.
Subjects / Keywords
Optimal transportation; Total variation; Image analysis