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...
| Publié dans: | 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: | Article en ligne |
| Langue: | English |
| Publié: |
2014
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Sujets: | Journal Article Research Support, U.S. Gov't, Non-P.H.S. |
| Accès en ligne |
Volltext |