Unsupervised saliency-guided SAR image change detection
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- 作者：Yaoguo Zheng ; zheng_yaoguo@163.com" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Licheng Jiao lchjiao@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Hongying Liu hyliu@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Xiangrong Zhang xrzhang@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Biao Hou avcodec@hotmail.com" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Shuang Wang shwang@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Unsupervised change detection ; Saliency map ; Principal component analysis ; K-means clustering ; Synthetic aperture radar (SAR) images
- 刊名：Pattern Recognition
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：61
- 期：Complete
- 页码：309-326
- 全文大小：7710 K
文摘
Saliency is used to guide the change detection of SAR images.
A framework from localization to recognition is proposed.
Experimental results show the well performance of SGK.