A Site Model Based Change Detection method for SAR Images

被引：0
|
作者：
Wang, Wei [1 ]
Shi, Jianhua [1 ]
Zhao, Lingjun [2 ]
Yan, Xingwei [2 ]
机构：
[1] Natl Univ Def Technol, Coll Adv Interdisciplinary Res, Changsha, Peoples R China
[2] Natl Univ Def Technol, Coll Elect Sci & Technol, Changsha, Peoples R China
来源：
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
ALGORITHM;
D O I：
10.1109/CVPRW.2019.00101
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a new method of site model based change detection is presented for multitemporal synthetic aperture radar (SAR) images. It first constructs a site model offline making use of a high resolution image of the fixed site, and then accurate registration is carried out between the model and the images. With the location information contained in the site model, the region of interest (ROI) can be extracted easily and robustly. Finally, the significant changes are obtained by comparing the invariant features extracted separately from the shapes of targets in ROI of two images. The experiment of change detection for two SAR images of airport demonstrated the validity of the proposed method.
引用
收藏
页码：738 / 742
页数：5
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