Bibliographic Metadata

Title
An efficient primal dual method for L1TV image restoration
AuthorDong, Yiqiu ; Hintermüller, Michael In der Gemeinsamen Normdatei der DNB nachschlagen ; Neri, Marrick
Published in
SIAM Journal on Imaging Sciences, 2009, Vol. 2, Issue 4, page 1168-1189
Edition
Publisher version
LanguageEnglish
Document typeJournal Article
Keywords (EN)deblurring / duality / l1-data fitting / random-valued impulse noise / salt-and-pepper noise / semismooth Newton / total variation regularization
Keywords (GND)Bildrekonstruktion / Optimierung / Online-Publikation
ISSN1936-4954
URNurn:nbn:at:at-ubg:3-975 Persistent Identifier (URN)
DOIdoi:10.1137/090758490 
Restriction-Information
 The work is publicly available
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An efficient primal dual method for L1TV image restoration [2.59 mb]
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Abstract (English)

Image restoration based on an l1-data-fitting term and edge preserving total variation regularization is considered. The associated nonsmooth energy minimization problem is handled by utilizing Fenchel duality and dual regularization techniques. The latter guarantee uniqueness of the dual solution and an efficient way for reconstructing a primal solution, i.e., the restored image, from a dual solution. For solving the resulting primal-dual system, a semismooth Newton solver is proposed and its convergence is studied. The paper ends with a report on restoration results obtained by the new algorithm for salt-and-pepper or random-valued impulse noise including blurring. A comparison with other methods is provided as well.

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