A general framework for regularized, similarity-based image restoration
Any image can be represented as a function defined on a weighted graph, in which the underlying structure of the image is encoded in kernel similarity and associated Laplacian matrices. In this paper, we develop an iterative graph-based framework for image restoration based on a new definition of th...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 23(2014), 12 vom: 05. Dez., Seite 5136-51 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2014
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article Research Support, U.S. Gov't, Non-P.H.S. |
| Online verfügbar |
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