Boosting Single Image Super-Resolution Learnt From Implicit Multi-Image Prior
Learning-based single image super-resolution (SISR) aims to learn a versatile mapping from low resolution (LR) image to its high resolution (HR) version. The critical challenge is to bias the network training towards continuous and sharp edges. For the first time in this work, we propose an implicit...
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Détails bibliographiques
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 30(2021) vom: 23., Seite 3240-3251
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| Auteur principal: |
Jin, Dingjian
(Auteur) |
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| Autres auteurs: |
Ji, Mengqi,
Xu, Lan,
Wu, Gaochang,
Wang, Liejun,
Fang, Lu |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2021
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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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