Unregistered Hyperspectral and Multispectral Image Fusion with Synchronous Nonnegative Matrix Factorization | |
Chen, Wenjing1,2; Lu, Xiaoqiang2 | |
2020 | |
会议日期 | 2020-10-16 |
会议地点 | Nanjing, China |
关键词 | Image fusion Nonnegative matrix factorization Hyperspectral image Multispectral image |
卷号 | 12305 LNCS |
DOI | 10.1007/978-3-030-60633-6_50 |
页码 | 602-614 |
英文摘要 | Recently, many methods have been proposed to generate a high spatial resolution (HR) hyperspectral image (HSI) by fusing HSI and multispectral image (MSI). Most methods need a precondition that HSI and MSI are well registered. However, in practice, it is hard to acquire registered HSI and MSI. In this paper, a synchronous nonnegative matrix factorization (SNMF) is proposed to directly fuse unregistered HSI and MSI. The proposed SNMF does not require the registration operation by modeling the abundances of unregistered HSI and MSI independently. Moreover, to exploit both HSI and MSI in the endmember optimization of the desired HR HSI, the unregistered HSI and MSI fusion is formulated as a bound-constrained optimization problem. A synchronous projected gradient method is proposed to solve this bound-constrained optimization problem. Experiments on both simulated and real data demonstrate that the proposed SNMF outperforms the state-of-the-art methods. © 2020, Springer Nature Switzerland AG. |
产权排序 | 1 |
会议录 | Pattern Recognition and Computer Vision - 3rd Chinese Conference, PRCV 2020, Proceedings
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会议录出版者 | Springer Science and Business Media Deutschland GmbH |
语种 | 英语 |
ISSN号 | 03029743;16113349 |
ISBN号 | 9783030606329 |
内容类型 | 会议论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/93766] ![]() |
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 | Lu, Xiaoqiang |
作者单位 | 1.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; |
推荐引用方式 GB/T 7714 | Chen, Wenjing,Lu, Xiaoqiang. Unregistered Hyperspectral and Multispectral Image Fusion with Synchronous Nonnegative Matrix Factorization[C]. 见:. Nanjing, China. 2020-10-16. |
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