The spectral-spatial joint learning for change detection in multispectral imagery | |
Zhang, Wuxia1,2; Lu, Xiaoqiang1 | |
刊名 | Remote Sensing |
2019-02 | |
卷号 | 11期号:3 |
关键词 | multispectral imagery spectral-spatial representation Siamese CNN feature fusion discrimination learning change detection |
ISSN号 | 20724292 |
DOI | 10.3390/rs11030240 |
产权排序 | 1 |
英文摘要 | Change detection is one of the most important applications in the remote sensing domain. More and more attention is focused on deep neural network based change detection methods. However, many deep neural networks based methods did not take both the spectral and spatial information into account. Moreover, the underlying information of fused features is not fully explored. To address the above-mentioned problems, a Spectral-Spatial Joint Learning Network (SSJLN) is proposed. SSJLN contains three parts: spectral-spatial joint representation, feature fusion, and discrimination learning. First, the spectral-spatial joint representation is extracted from the network similar to the Siamese CNN (S-CNN). Second, the above-extracted features are fused to represent the difference information that proves to be effective for the change detection task. Third, the discrimination learning is presented to explore the underlying information of obtained fused features to better represent the discrimination. Moreover, we present a new loss function that considers both the losses of the spectral-spatial joint representation procedure and the discrimination learning procedure. The effectiveness of our proposed SSJLN is verified on four real data sets. Extensive experimental results show that our proposed SSJLN can outperform the other state-of-the-art change detection methods. © 2019 by the authors. |
语种 | 英语 |
出版者 | MDPI AG, Postfach, Basel, CH-4005, Switzerland |
WOS记录号 | WOS:000459944400028 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/31265] |
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.Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; 710119, China; 2.University of Chinese Academy of Sciences, Beijing; 100049, China |
推荐引用方式 GB/T 7714 | Zhang, Wuxia,Lu, Xiaoqiang. The spectral-spatial joint learning for change detection in multispectral imagery[J]. Remote Sensing,2019,11(3). |
APA | Zhang, Wuxia,&Lu, Xiaoqiang.(2019).The spectral-spatial joint learning for change detection in multispectral imagery.Remote Sensing,11(3). |
MLA | Zhang, Wuxia,et al."The spectral-spatial joint learning for change detection in multispectral imagery".Remote Sensing 11.3(2019). |
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