Domain Adaptation for Underwater Image Enhancement
Recently, learning-based algorithms have shown impressive performance in underwater image enhancement. Most of them resort to training on synthetic data and obtain outstanding performance. However, these deep methods ignore the significant domain gap between the synthetic and real data (i.e., inter-...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 32(2023) vom: 04., Seite 1442-1457
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| 1. Verfasser: |
Wang, Zhengyong
(VerfasserIn) |
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| Weitere Verfasser: |
Shen, Liquan,
Xu, Mai,
Yu, Mei,
Wang, Kun,
Lin, Yufei |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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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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