AFCANet: An adaptive feature concatenate attention network for multi-focus image fusion
文献类型：期刊论文
| 作者 | Liu, Shuaiqi1,2,4; Peng, Weijian1,4; Liu, Yali1,4; Zhao, Jie1,4; Su, Yonggang1,4; Zhang, Yudong3 |
| 刊名 | JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
 |
| 出版日期 | 2023-10-01 |
| 卷号 | 35期号:9页码:22 |
| ISSN号 | 1319-1578 |
| 关键词 | Multi -focus image fusion Unsupervised training Adaptive feature concatenate Attention module |
| DOI | 10.1016/j.jksuci.2023.101751 |
| 通讯作者 | Su, Yonggang(ygsu0726@163.com) ; Zhang, Yudong() |
| 英文摘要 | For multi-focus image fusion, the existing deep learning based methods cannot effectively learn the texture features and semantic information of the source image to generate high-quality fused images. Thus, we develop a new adaptive feature concatenate attention network named AFCANet, which adaptively learns cross-layer features and retains the texture features and semantic information of images to generate visually appealing fully focused images. In AFCANet, the encoder-decoder network is used as the backbone network. In the unsupervised training stage, an adaptive cross-layer skip connection mode is designed, and a cross-layer adaptive coordinate attention module is built to acquire meaningful information from the image along with ignoring unimportant information to obtain a better image fusion effect. In addition, in the middle of the encoder-decoder network, we also introduce an effective channel attention module to fully learn the output of the encoder, and accelerate network convergence. In the inference stage, we apply the pixel-based spatial frequency fusion rules to fuse the adaptive features learned by the encoder, which can successfully combine the texture and semantic information of the image and produce a more precise decision map. Extensive experiments on public datasets and the HBU-CVMDSP dataset show that our AFCANet can effectively improve the accuracy of the decision map in the focus and defocus regions, as well as improve the ability to retain the abundant details and edge features of the source image.(c) 2023 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| WOS关键词 | ALGORITHM |
| 资助项目 | Natural Science Foun- dation of Hebei Province[F2022201055] ; Natural Science Foun- dation of Hebei Province[2022M713361] ; National Natural Science Foundation of China[62172139] ; Natural Science Foundation of Hebei Province[F2022201055] ; China Postdoctoral[2022M713361] ; Hebei University Research and Innovation Team Support Project[IT2023B05] ; Natural Science Interdisciplinary Research Program of Hebei University[DXK202102] ; Open Project Program of the National Laboratory of Pattern Recognition (NLPR)[202200007] ; High-Performance Computing Center of Hebei University |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:001082388200001 |
| 资助机构 | Natural Science Foun- dation of Hebei Province ; National Natural Science Foundation of China ; Natural Science Foundation of Hebei Province ; China Postdoctoral ; Hebei University Research and Innovation Team Support Project ; Natural Science Interdisciplinary Research Program of Hebei University ; Open Project Program of the National Laboratory of Pattern Recognition (NLPR) ; High-Performance Computing Center of Hebei University |
| 源URL | [http://ir.ia.ac.cn/handle/173211/52974]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Su, Yonggang; Zhang, Yudong |
| 作者单位 | 1.Machine Vis Technol Innovat Ctr Hebei Prov, Baoding 071000, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 3.Univ Leicester, Sch Comp & Math Sci, Leicester LE1 7RH, England 4.Hebei Univ, Coll Elect & Informat Engn, Baoding 071000, Hebei, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Shuaiqi,Peng, Weijian,Liu, Yali,et al. AFCANet: An adaptive feature concatenate attention network for multi-focus image fusion[J]. JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES,2023,35(9):22. |
| APA | Liu, Shuaiqi,Peng, Weijian,Liu, Yali,Zhao, Jie,Su, Yonggang,&Zhang, Yudong.(2023).AFCANet: An adaptive feature concatenate attention network for multi-focus image fusion.JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES,35(9),22. |
| MLA | Liu, Shuaiqi,et al."AFCANet: An adaptive feature concatenate attention network for multi-focus image fusion".JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 35.9(2023):22. |
入库方式： OAI收割
来源：自动化研究所
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