Nonparametric Bayesian dictionary learning for analysis of noisy and incomplete images
Nonparametric Bayesian methods are considered for recovery of imagery based upon compressive, incomplete, and/or noisy measurements. A truncated beta-Bernoulli process is employed to infer an appropriate dictionary for the data under test and also for image recovery. In the context of compressive se...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 21(2012), 1 vom: 21. Jan., Seite 130-44
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| 1. Verfasser: |
Zhou, Mingyuan
(VerfasserIn) |
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| Weitere Verfasser: |
Chen, Haojun,
Paisley, John,
Ren, Lu,
Li, Lingbo,
Xing, Zhengming,
Dunson, David,
Sapiro, Guillermo,
Carin, Lawrence |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2012
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article
Research Support, U.S. Gov't, Non-P.H.S. |
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