Multisource Remote Sensing Data Classification With Graph Fusion Network
文献类型：期刊论文
| 作者 | Du, Xingqian1; Zheng, Xiangtao2 ; Lu, Xiaoqiang3; Doudkin, Alexander A.4
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| 刊名 | IEEE Transactions on Geoscience and Remote Sensing
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| 出版日期 | 2021 |
| ISSN号 | 01962892;15580644 |
| 关键词 | Classification deep learning hyperspectral image (HSI) light detection and ranging (LiDAR) remote sensing |
| DOI | 10.1109/TGRS.2020.3047130 |
| 产权排序 | 1 |
| 英文摘要 | The land cover classification has been an important task in remote sensing. With the development of various sensors technologies, carrying out classification work with multisource remote sensing (MSRS) data has shown an advantage over using a single type of data. Hyperspectral images (HSIs) are able to represent the spectral properties of land cover, which is quite common for land cover understanding. Light detection and ranging (LiDAR) images contain altitude information of the ground, which is greatly helpful with urban scene analysis. Current HSI and LiDAR fusion methods perform feature extraction and feature fusion separately, which cannot well exploit the correlation of data sources. In order to make full use of the correlation of multisource data, an unsupervised feature extraction-fusion network for HSI and LiDAR, which utilizes feature fusion to guide the feature extraction procedure, is proposed in this article. More specifically, the network takes multisource data as input and directly output the unified fused feature. A multimodal graph is constructed for feature fusion, and graph-based loss functions including Laplacian loss and t-distributed stochastic neighbor embedding (t-SNE) loss are utilized to constrain the feature extraction network. Experimental results on several data sets demonstrate the proposed network can achieve more excellent classification performance than some state-of-the-art methods. IEEE |
| 语种 | 英语 |
| 出版者 | Institute of Electrical and Electronics Engineers Inc. |
| 源URL | [http://ir.opt.ac.cn/handle/181661/94278]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 作者单位 | 1.Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China, and also with the University of Chinese Academy of Sciences, Beijing 100049, China.; 2.Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China (e-mail: xiangtaoz@gmail.com); 3.Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.; 4.Laboratory of System Identification, United Institute of Informatics Problems of the National Academy of Sciences of Belarus, 220012 Minsk, Belarus, and also with the Department of Computers, Belarusian State University of Informatics and Radioelectronics (BSUIR), 220012 Minsk, Belarus. |
| 推荐引用方式 GB/T 7714 | Du, Xingqian,Zheng, Xiangtao,Lu, Xiaoqiang,et al. Multisource Remote Sensing Data Classification With Graph Fusion Network[J]. IEEE Transactions on Geoscience and Remote Sensing,2021. |
| APA | Du, Xingqian,Zheng, Xiangtao,Lu, Xiaoqiang,&Doudkin, Alexander A..(2021).Multisource Remote Sensing Data Classification With Graph Fusion Network.IEEE Transactions on Geoscience and Remote Sensing. |
| MLA | Du, Xingqian,et al."Multisource Remote Sensing Data Classification With Graph Fusion Network".IEEE Transactions on Geoscience and Remote Sensing (2021). |
入库方式： OAI收割
来源：西安光学精密机械研究所
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