MsIFT: Multi-Source Image Fusion Transformer

doi:10.3390/rs14164062

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 遥感图像处理团队

	MsIFT: Multi-Source Image Fusion Transformer
	Zhang, Xin 2,3; Jiang, Hangzhi 2,3; Xu, Nuo 2,3; Ni, Lei 1; Huo, Chunlei 2,3; Pan, Chunhong 2,3
刊名	REMOTE SENSING
	2022-08-01
卷号	14 期号:16 页码:19
关键词	transformer multi-source image fusion non-local
DOI	10.3390/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.
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关键词	SHIP CLASSIFICATION ; LIDAR
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
内容类型	期刊论文
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.