OPT OpenIR  > 光谱成像技术研究室
The spectral-spatial joint learning for change detection in multispectral imagery
Zhang, Wuxia1,2; Lu, Xiaoqiang1
作者部门光谱成像技术研究室
2019-02
发表期刊Remote Sensing
ISSN20724292
卷号11期号:3
产权排序1
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.

关键词multispectral imagery spectral-spatial representation Siamese CNN feature fusion discrimination learning change detection
DOI10.3390/rs11030240
收录类别SCI ; EI
语种英语
WOS记录号WOS:000459944400028
出版者MDPI AG, Postfach, Basel, CH-4005, Switzerland
EI入藏号20190706505805
引用统计
被引频次:54[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/31265
专题光谱成像技术研究室
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).
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
The spectral-spatial(13482KB)期刊论文出版稿限制开放CC BY-NC-SA请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Zhang, Wuxia]的文章
[Lu, Xiaoqiang]的文章
百度学术
百度学术中相似的文章
[Zhang, Wuxia]的文章
[Lu, Xiaoqiang]的文章
必应学术
必应学术中相似的文章
[Zhang, Wuxia]的文章
[Lu, Xiaoqiang]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

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。