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Global Total Variation Minimization

Dibos, Françoise; Koepfler, Georges (2000), Global Total Variation Minimization, SIAM Journal on Numerical Analysis, 37, 2, p. 646-664. http://dx.doi.org/10.1137/S0036142998334838

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Type
Article accepté pour publication ou publié
Date
2000
Nom de la revue
SIAM Journal on Numerical Analysis
Volume
37
Numéro
2
Éditeur
SIAM
Pages
646-664
Identifiant publication
Métadonnées
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Auteur(s)
Dibos, Françoise
Koepfler, Georges
Résumé (EN)
The minimization of the total variation is an important tool of image processing. A lot of authors have addressed the problem and developed algorithms for image denoising. In this paper we present an alternative approach of the total variation minimization problem. After an introduction to the topic and a review of related work, we give a short development of the bounded variation (BV) background. Then we present our global total variation minimization model and proof its validity. Furthermore we introduce a practical algorithm which handles digital image data and we give experimental results.
Mots-clés
total variation; image denoising; minimization; level set