Underwater Image Restoration and Enhancement via Residual Two-Fold Attention Networks
Underwater images or videos are common but essential information carrier for observation, fishery industry and intelligent analysis system in underwater vehicles. But underwater images are usually suffering from more complex imaging interfering impacts. This paper describes a novel residual two-fold...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2020-11-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/125945762/view |
| _version_ | 1818539167329550336 |
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| author | Bo Fu Liyan Wang Ruizi Wang Shilin Fu Fangfei Liu Xin Liu |
| author_facet | Bo Fu Liyan Wang Ruizi Wang Shilin Fu Fangfei Liu Xin Liu |
| author_sort | Bo Fu |
| collection | DOAJ |
| description | Underwater images or videos are common but essential information carrier for observation, fishery industry and intelligent analysis system in underwater vehicles. But underwater images are usually suffering from more complex imaging interfering impacts. This paper describes a novel residual two-fold attention networks for underwater image restoration and enhancement to eliminate the interference of color deviation and noise at the same time. In our network framework, nonlocal attention and channel attention mechanisms are respectively embedded to mine and enhance more features. Quantitative and qualitative experiment data demonstrates that our proposed approach generates more visually appealing images, and also provides higher objective evaluation index score. |
| first_indexed | 2024-12-11T21:38:28Z |
| format | Article |
| id | doaj.art-94f1d2280d98455faad623828b9709d0 |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-12-11T21:38:28Z |
| publishDate | 2020-11-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-94f1d2280d98455faad623828b9709d02022-12-22T00:49:55ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832020-11-0114110.2991/ijcis.d.201102.001Underwater Image Restoration and Enhancement via Residual Two-Fold Attention NetworksBo FuLiyan WangRuizi WangShilin FuFangfei LiuXin LiuUnderwater images or videos are common but essential information carrier for observation, fishery industry and intelligent analysis system in underwater vehicles. But underwater images are usually suffering from more complex imaging interfering impacts. This paper describes a novel residual two-fold attention networks for underwater image restoration and enhancement to eliminate the interference of color deviation and noise at the same time. In our network framework, nonlocal attention and channel attention mechanisms are respectively embedded to mine and enhance more features. Quantitative and qualitative experiment data demonstrates that our proposed approach generates more visually appealing images, and also provides higher objective evaluation index score.https://www.atlantis-press.com/article/125945762/viewDeep residual networkUnderwater image restorationNonlocal attentionChannel attentionImage de-noisingImage color enhancement |
| spellingShingle | Bo Fu Liyan Wang Ruizi Wang Shilin Fu Fangfei Liu Xin Liu Underwater Image Restoration and Enhancement via Residual Two-Fold Attention Networks International Journal of Computational Intelligence Systems Deep residual network Underwater image restoration Nonlocal attention Channel attention Image de-noising Image color enhancement |
| title | Underwater Image Restoration and Enhancement via Residual Two-Fold Attention Networks |
| title_full | Underwater Image Restoration and Enhancement via Residual Two-Fold Attention Networks |
| title_fullStr | Underwater Image Restoration and Enhancement via Residual Two-Fold Attention Networks |
| title_full_unstemmed | Underwater Image Restoration and Enhancement via Residual Two-Fold Attention Networks |
| title_short | Underwater Image Restoration and Enhancement via Residual Two-Fold Attention Networks |
| title_sort | underwater image restoration and enhancement via residual two fold attention networks |
| topic | Deep residual network Underwater image restoration Nonlocal attention Channel attention Image de-noising Image color enhancement |
| url | https://www.atlantis-press.com/article/125945762/view |
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