Adaptive learning attention network for underwater image enhancement
文献类型:期刊论文
作者 | Liu SB(刘世本)1,2; Fan HJ(范慧杰)1,2; Lin S(林森)1,2; Wang Q(王强)2,3; Ding ND(丁乃达); Tang YD(唐延东)1,2 |
刊名 | IEEE Robotics and Automation Letters |
出版日期 | 2022 |
卷号 | 7期号:2页码:5326-5333 |
ISSN号 | 2377-3766 |
关键词 | Attention mechanism computer vision for automation deep learning methods underwater image enhancement |
产权排序 | 1 |
英文摘要 | Underwater images suffer from color casts and low illumination due to the scattering and absorption of light as it propagates in water. These problems can interfere with underwater vision tasks, such as recognition and detection. We propose an adaptive learning attention network for underwater image enhancement, named LANet, to solve these degradation issues. First, a multiscale fusion module is proposed to combine different spatial information. Second, we design a novel parallel attention module(PAM) to focus on the illuminated features and more significant color information coupled with the pixel and channel attention. Then, an adaptive learning module(ALM) can retain the shallow information and adaptively learn important feature information. Further, we utilize a multinomial loss function that is formed by mean absolute error and perceptual loss. Finally, we introduce an asynchronous training mode to promote the network's performance of multinomial loss function. Qualitative analysis and quantitative evaluations show the excellent performance of our method on different underwater datasets. The code is available at: https://github.com/LiuShiBen/LANet. |
WOS关键词 | COLOR CORRECTION ; RESTORATION ; QUALITY |
资助项目 | NationalNatural Science Foundation of China[61991413] ; NationalNatural Science Foundation of China[U20A20200] ; NationalNatural Science Foundation of China[62073205] ; Youth Innovation Promotion Association of the Chinese Academy of Sciences[2019203] |
WOS研究方向 | Robotics |
语种 | 英语 |
WOS记录号 | WOS:000770005100021 |
资助机构 | NationalNatural Science Foundation of China under Grants 61991413, U20A20200, and 62073205 ; Youth Innovation Promotion Association of the Chinese Academy of Sciences under Grant 2019203 |
源URL | [http://ir.sia.cn/handle/173321/30607] |
专题 | 沈阳自动化研究所_机器人学研究室 |
通讯作者 | Fan HJ(范慧杰) |
作者单位 | 1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, shenyang, China, 110016 3.Key Laboratory of Manufacturing Industrial Integrated, Shenyang University, Shenyang 110016, China |
推荐引用方式 GB/T 7714 | Liu SB,Fan HJ,Lin S,et al. Adaptive learning attention network for underwater image enhancement[J]. IEEE Robotics and Automation Letters,2022,7(2):5326-5333. |
APA | Liu SB,Fan HJ,Lin S,Wang Q,Ding ND,&Tang YD.(2022).Adaptive learning attention network for underwater image enhancement.IEEE Robotics and Automation Letters,7(2),5326-5333. |
MLA | Liu SB,et al."Adaptive learning attention network for underwater image enhancement".IEEE Robotics and Automation Letters 7.2(2022):5326-5333. |
入库方式: OAI收割
来源:沈阳自动化研究所
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