Attention-Based Multi-Branch Network for Low-Light Image Enhancement | |
Jiao, Yin1,2; Zheng, Xiangtao2; Lu, Xiaoqiang2 | |
2021-03-26 | |
会议名称 | 2nd IEEE International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021 |
会议录名称 | 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021 |
页码 | 401-407 |
会议日期 | 2021-03-26 |
会议地点 | Nanchang, China |
出版者 | Institute of Electrical and Electronics Engineers Inc. |
产权排序 | 1 |
摘要 | Low-light conditions make the obtained images suffer a series of degradation, such as low contrast, noise interference and color distortion. Many previous learning-based methods have made remarkable progress, but they may still produce unsatisfactory results for ignoring noise in low-light regions. An attention-based multi-branch network is proposed, which can adequately enhance the image and suppress latent noise. The proposed method firstly estimates illumination component and reflectance component through a decomposition process. Then the illumination component is brightened to reconstruct the global lighting distribution, and the reflectance component is restored to remove noise and maintain details. A lightweight but effective attention block is employed to guide the restoration of the reflectance component, so as to concentrate on the distribution of lighting in different regions and effectively suppress noise in the dim environment. Extensive experiments on several datasets show the proposed method can achieve good results compared with classic and state-of-the-art methods. © 2021 IEEE. |
关键词 | low-light enhancement multi-branch network retinex theory attention |
作者部门 | 光谱成像技术研究室 |
收录类别 | EI |
ISBN号 | 9780738131221 |
语种 | 英语 |
EI入藏号 | 20211710245631 |
文献类型 | 会议论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/94689 |
专题 | 光谱成像技术研究室 |
作者单位 | 1.University of Chinese Academy of Sciences, Beijing, China 2.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Key Laboratory of Spectral Imaging Technology Cas, Xi'an, China |
推荐引用方式 GB/T 7714 | Jiao, Yin,Zheng, Xiangtao,Lu, Xiaoqiang. Attention-Based Multi-Branch Network for Low-Light Image Enhancement[C]:Institute of Electrical and Electronics Engineers Inc.,2021:401-407. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Attention-Based Mult(1348KB) | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 |
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