A new reweighted [InlineEquation not available: see fulltext.] minimization algorithm for image deblurring: Doc 1111
In this paper, A new reweighted [InlineEquation not available: see fulltext.] minimization algorithm for image deblurring is proposed. The algorithm is based on a generalized inverse iteration and linearized Bregman iteration, which is used for the weighted [InlineEquation not available: see fulltex...
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Veröffentlicht in: | Journal of inequalities and applications 2014-06, Vol.2014, p.1 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | In this paper, A new reweighted [InlineEquation not available: see fulltext.] minimization algorithm for image deblurring is proposed. The algorithm is based on a generalized inverse iteration and linearized Bregman iteration, which is used for the weighted [InlineEquation not available: see fulltext.] minimization problem [InlineEquation not available: see fulltext.]. In the computing process, the effective using of signal information can make up the detailed features of image, which may be lost in the deblurring process. Numerical experiments confirm that the new reweighted algorithm for image restoration is effective and competitive to the recent state-of-the-art algorithms.[PUBLICATION ABSTRACT] |
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ISSN: | 1025-5834 1029-242X |
DOI: | 10.1186/1029-242X-2014-238 |