Tensor Completion via Complementary Global, Local, and Nonlocal Priors
Completing missing entries in multidimensional visual data is a typical ill-posed problem that requires appropriate exploitation of prior information of the underlying data. Commonly used priors can be roughly categorized into three classes: global tensor low-rankness, local properties, and nonlocal...
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Détails bibliographiques
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 31(2022) vom: 18., Seite 984-999
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| Auteur principal: |
Zhao, Xi-Le
(Auteur) |
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| Autres auteurs: |
Yang, Jing-Hua,
Ma, Tian-Hui,
Jiang, Tai-Xiang,
Ng, Michael K,
Huang, Ting-Zhu |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2022
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Sujets: | Journal Article |
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