Titelaufnahme

Titel
A nonlinear multigrid solver with line Gauss-Seidel-semismooth-Newton smoother for the Fenchel-pre-dual in total variation based image restoration
Verfasser/ VerfasserinChen, Ke ; Dong, Yiqiu ; Hintermüller, Michael In der Gemeinsamen Normdatei der DNB nachschlagen
Erschienen in
Inverse Problems and Imaging, Springfield, Mo., 2011, Jg. 5, H. 2, S. 323-339
ErschienenAIMS
SpracheEnglisch
DokumenttypAufsatz in einer Zeitschrift
Schlagwörter (EN)Image restoration / total variation regularization / duality / multigrid method
URNurn:nbn:at:at-ubg:3-669 Persistent Identifier (URN)
DOIdoi:10.3934/ipi.2011.5.323 
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A nonlinear multigrid solver with line Gauss-Seidel-semismooth-Newton smoother for the Fenchel-pre-dual in total variation based image restoration [0.62 mb]
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Zusammenfassung (Englisch)

Based on the Fenchel pre-dual of the total variation model, a nonlinear multigrid algorithm for image denoising is proposed. Due to the structure of the differential operator involved in the Euler-Lagrange equations of the dual models, line Gauss-Seidel-semismooth-Newton step is utilized as the smoother, which provides rather good smoothing rates. The paper ends with a report on numerical results and a comparison with a very recent nonlinear multigrid solver based on Chambolle's Iteration.

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