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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Bibliographische Detailangaben
| Veröffentlicht in: | 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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| 1. Verfasser: |
Jin, Dingjian
(VerfasserIn) |
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| Weitere Verfasser: |
Ji, Mengqi,
Xu, Lan,
Wu, Gaochang,
Wang, Liejun,
Fang, Lu |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2021
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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 |
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