Total generalized variation for piecewise constant functions on triangular meshes with applications in imaging
Multiplicative noise removal problems have attracted much attention in recent years. Unlike additive noise removal problems, the noise is multiplied to the orginal image, so almost all information of the original image may disappear in the observed image. The main aim of this paper is to propose and...
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| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
February 27, 2023
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| In: |
SIAM journal on imaging sciences
Year: 2023, Jahrgang: 16, Heft: 1, Pages: 313-339 |
| ISSN: | 1936-4954 |
| DOI: | 10.1137/22M1505281 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1137/22M1505281 Verlag, lizenzpflichtig, Volltext: https://epubs.siam.org/doi/10.1137/22M1505281 
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| Verfasserangaben: | Lukas Baumgärtner, Ronny Bergmann, Roland Herzog, Stephan Schmidt, and José Vidal-Núnez |
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| 520 | |a Multiplicative noise removal problems have attracted much attention in recent years. Unlike additive noise removal problems, the noise is multiplied to the orginal image, so almost all information of the original image may disappear in the observed image. The main aim of this paper is to propose and study a strictly convex objective function for multiplicative noise removal problems. We also incorporate the modified total variation regularization in the objective function to recover image edges. We develop an alternating minimization algorithm to find the minimizer of such an objective function efficiently and also show the convergence of the minimizing method. Our experimental results show that the quality of images denoised by the proposed method is quite good. | ||
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