Unsupervised saliency-guided SAR image change detection

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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 author}Author Vitae ; Licheng Jiao ^{lchjiao@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Hongying Liu ^{hyliu@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Xiangrong Zhang ^{xrzhang@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Biao Hou ^{avcodec@hotmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Shuang Wang ^{shwang@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author 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.

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