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 / ConférenceExternal document link
https://hal.science/hal-04113284Date
2023Conference title
Geometric Science of Information. GSI 2023Conference date
2023-08Conference city
Saint MaloConference country
FranceBook title
Geometric Science of Information. GSI 2023. Lecture Notes in Computer Science, vol 14071Book author
Nielsen, F., Barbaresco, F. (eds)Publisher
Springer International Publishing
Published in
Berlin Heidelberg
ISBN
978-3-031-38270-3
Number of pages
624Pages
610-619
Publication identifier
Metadata
Show full item recordAuthor(s)
Chambolle, Antonin
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Duval, Vincent

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 analysisRelated items
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