{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T14:54:09Z","timestamp":1785855249907,"version":"3.56.0"},"reference-count":46,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T00:00:00Z","timestamp":1686614400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Natural Science Foundation of Anhui Province","award":["2208085MF156"],"award-info":[{"award-number":["2208085MF156"]}]},{"name":"the Natural Science Foundation of Anhui Province","award":["JZ2022HGTB0329"],"award-info":[{"award-number":["JZ2022HGTB0329"]}]},{"name":"the Natural Science Foundation of Anhui Province","award":["2019200P4001"],"award-info":[{"award-number":["2019200P4001"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2208085MF156"],"award-info":[{"award-number":["2208085MF156"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["JZ2022HGTB0329"],"award-info":[{"award-number":["JZ2022HGTB0329"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2019200P4001"],"award-info":[{"award-number":["2019200P4001"]}]},{"name":"the Aeronautical Science Foundation of China","award":["2208085MF156"],"award-info":[{"award-number":["2208085MF156"]}]},{"name":"the Aeronautical Science Foundation of China","award":["JZ2022HGTB0329"],"award-info":[{"award-number":["JZ2022HGTB0329"]}]},{"name":"the Aeronautical Science Foundation of China","award":["2019200P4001"],"award-info":[{"award-number":["2019200P4001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In the field of image fusion, spatial detail blurring and color distortion appear in synthetic aperture radar (SAR) images and multispectral (MS) during the traditional fusion process due to the difference in sensor imaging mechanisms. To solve this problem, this paper proposes a fusion method for SAR images and MS images based on a convolutional neural network. In order to make use of the spatial information and different scale feature information of high-resolution SAR image, a dual-channel feature extraction module is constructed to obtain a SAR image feature map. In addition, different from the common direct addition strategy, an attention-based feature fusion module is designed to achieve spectral fidelity of the fused images. In order to obtain better spectral and spatial retention ability of the network, an unsupervised joint loss function is designed to train the network. In this paper, the Sentinel 1 SAR images and Landsat 8 MS images are used as datasets for experiments. The experimental results show that the proposed algorithm has better performance in quantitative and visual representation when compared with traditional fusion methods and deep learning algorithms.<\/jats:p>","DOI":"10.3390\/rs15123091","type":"journal-article","created":{"date-parts":[[2023,6,14]],"date-time":"2023-06-14T02:01:40Z","timestamp":1686708100000},"page":"3091","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["DAFCNN: A Dual-Channel Feature Extraction and Attention Feature Fusion Convolution Neural Network for SAR Image and MS Image Fusion"],"prefix":"10.3390","volume":"15","author":[{"given":"Jiahao","family":"Luo","sequence":"first","affiliation":[{"name":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an 710071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengdao","family":"Xing","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China"},{"name":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.inffus.2016.03.003","article-title":"A review of remote sensing image fusion methods","volume":"32","author":"Ghassemian","year":"2016","journal-title":"Inf. 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