Change detection in very high-resolution images based on ensemble CNNs
文献类型：期刊论文
| 作者 | Zhang, Xinlong2; Fan, Rui2; Ma, Lei2; Liao, Xiaohan1; Chen, Xiuwan3 |
| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2020-06-17 |
| 卷号 | 41期号:12页码:4755-4777 |
| ISSN号 | 0143-1161 |
| DOI | 10.1080/01431161.2020.1723818 |
| 通讯作者 | Zhang, Xinlong(mtxinlong@126.com) |
| 英文摘要 | This paper presents a novel change detection method for very-high-resolution images based on deep learning. In the method, an ensemble CNN change detection framework is proposed. Different from other deep learning change detection methods, samples of changed and unchanged regions of two very-high-resolution images acquired at different times are fed into two CNN. The discriminative deep metric learning based on dissimilarity degree is used to adjust discriminative distance metric of two CNN output layers quantitatively, under which the distance of unchanged samples becomes smaller and that of changed samples becomes higher, respectively. During its training procedure, cost module function based on dissimilarity degree of samples is used to train the ensemble CNN and high-level and abstract features of changed and unchanged pair of samples are driven to learn by the proposed framework. After training, the discriminative distance of unchanged samples becomes smaller and that of changed samples becomes larger. The proposed method justifies the changed and unchanged area of original images and change detection results can be obtained. Experiments on real datasets and theoretical analysis validate the effectiveness and superiority of the proposed method. |
| WOS关键词 | LAND-COVER CHANGE ; CLASSIFICATION ; PIXEL ; MODEL |
| 资助项目 | National key research and development program of China[2017YFB0503005] ; National Natural Science Foundation of China[41771388] |
| WOS研究方向 | Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000517366000001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National key research and development program of China ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/132640]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Xinlong |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China 2.China Elect Technol Grp Corp, China Acad Elect & Informat Technol, Beijing, Peoples R China 3.Peking Univ, Sch Earth & Space Sci, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Xinlong,Fan, Rui,Ma, Lei,et al. Change detection in very high-resolution images based on ensemble CNNs[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2020,41(12):4755-4777. |
| APA | Zhang, Xinlong,Fan, Rui,Ma, Lei,Liao, Xiaohan,&Chen, Xiuwan.(2020).Change detection in very high-resolution images based on ensemble CNNs.INTERNATIONAL JOURNAL OF REMOTE SENSING,41(12),4755-4777. |
| MLA | Zhang, Xinlong,et al."Change detection in very high-resolution images based on ensemble CNNs".INTERNATIONAL JOURNAL OF REMOTE SENSING 41.12(2020):4755-4777. |
入库方式： OAI收割
来源：地理科学与资源研究所
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