WEIGHTED SPARSITY CONSTRAINT TENSOR FACTORIZATION FOR HYPERSPECTRAL UNMIXING | |
Yuan, Yuan3; Dong, Le1,2 | |
2021 | |
会议日期 | 2021-07-12 |
会议地点 | Brussels, Belgium |
关键词 | Hyperspectral unmixing tensor factorization total variation sparse characteristics |
卷号 | 2021-July |
DOI | 10.1109/IGARSS47720.2021.9553154 |
页码 | 3333-3336 |
英文摘要 | Recently, the unmixing methods based on non-negative tensor factorization (NTF) have received a lot of attention. Many NTF-based methods combine total variation (TV) regularization, aiming at maintaining the smoothness of the abundance maps to improve the performance of unmixing. However, the existing TV regularization ignores the sparsity sharing on the spatial difference images among different bands. To tackle this issue, a weighted total variation regularizer on the spatial difference maps of abundances is proposed in this paper, which uses the L2,1 norm to explore the sparse structure in abundances along the spectral dimension. In addition, the L1/2 norm is used to enhance the spatial sparsity of abundances. The proposed method can not only enhance the sparsity in abundances, but also keep the spatial similarity characteristics of data. Compared with the existing popular methods, the proposed method has superior performance on both synthetic data and real data. © 2021 IEEE. |
产权排序 | 2 |
会议录 | IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings |
会议录出版者 | Institute of Electrical and Electronics Engineers Inc. |
语种 | 英语 |
ISBN号 | 9781665403696 |
内容类型 | 会议论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/95803] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
通讯作者 | Yuan, Yuan |
作者单位 | 1.University of Chinese Academy of Sciences, Beijing; 100049, China 2.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Shannxi, Xi'an; 710119, China; 3.School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an; 710072, China; |
推荐引用方式 GB/T 7714 | Yuan, Yuan,Dong, Le. WEIGHTED SPARSITY CONSTRAINT TENSOR FACTORIZATION FOR HYPERSPECTRAL UNMIXING[C]. 见:. Brussels, Belgium. 2021-07-12. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论