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MsIFT: Multi-Source Image Fusion Transformer

文献类型：期刊论文

作者Zhang, Xin2,3; Jiang, Hangzhi2,3; Xu, Nuo2,3; Ni, Lei1; Huo, Chunlei2,3; Pan, Chunhong2,3
刊名REMOTE SENSING
出版日期2022-08-01
卷号14期号:16页码:19
关键词transformer multi-source image fusion non-local
DOI10.3390/rs14164062
通讯作者Huo, Chunlei(clhuo@nlpr.ia.ac.cn)
英文摘要Multi-source image fusion is very important for improving image representation ability since its essence relies on the complementarity between multi-source information. However, feature-level image fusion methods based on the convolution neural network are impacted by the spatial misalignment between image pairs, which leads to the semantic bias in merging features and destroys the representation ability of the region-of-interests. In this paper, a novel multi-source image fusion transformer (MsIFT) is proposed. Due to the inherent global attention mechanism of the transformer, the MsIFT has non-local fusion receptive fields, and it is more robust to spatial misalignment. Furthermore, multiple classification-based downstream tasks (e.g., pixel-wise classification, image-wise classification and semantic segmentation) are unified in the proposed MsIFT framework, and the fusion module architecture is shared by different tasks. The MsIFT achieved state-of-the-art performances on the image-wise classification dataset VAIS, semantic segmentation dataset SpaceNet 6 and pixel-wise classification dataset GRSS-DFC-2013. The code and trained model are being released upon the publication of the work.
WOS关键词SHIP CLASSIFICATION ; LIDAR
资助项目National Natural Science Foundation of China[62071466] ; Fund of National Key Laboratory of Science and Technology on Remote Sensing Information and Imagery Analysis, Beijing Research Institute of Uranium Geology[6142A010402] ; Guangxi Natural Science Foundation[2018GXNSFBA281086]
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者MDPI
WOS记录号WOS:000845420000001
资助机构National Natural Science Foundation of China ; Fund of National Key Laboratory of Science and Technology on Remote Sensing Information and Imagery Analysis, Beijing Research Institute of Uranium Geology ; Guangxi Natural Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/50032]  
专题自动化研究所_模式识别国家重点实验室_遥感图像处理团队
通讯作者Huo, Chunlei
作者单位1.Beijing Inst Remote Sensing, Beijing 100085, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Xin,Jiang, Hangzhi,Xu, Nuo,et al. MsIFT: Multi-Source Image Fusion Transformer[J]. REMOTE SENSING,2022,14(16):19.
APA Zhang, Xin,Jiang, Hangzhi,Xu, Nuo,Ni, Lei,Huo, Chunlei,&Pan, Chunhong.(2022).MsIFT: Multi-Source Image Fusion Transformer.REMOTE SENSING,14(16),19.
MLA Zhang, Xin,et al."MsIFT: Multi-Source Image Fusion Transformer".REMOTE SENSING 14.16(2022):19.

入库方式： OAI收割

来源：自动化研究所

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