Removing Atmospheric Turbulence via Deep Adversarial Learning
Restoring images degraded due to atmospheric turbulence is challenging as it consists of several distortions. Several deep learning methods have been proposed to minimize atmospheric distortions that consist of a single-stage deep network. However, we find that a single-stage deep network is insuffi...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 31(2022) vom: 23., Seite 2633-2646 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2022
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
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