Multi-temporal SAR Images Change Detection Based on Nonsubsampled Contourlet Transform

被引：0
|
作者：
Lei, Lin [1 ]
Sui, Yinling [1 ]
Zou, Huanxin [1 ]
Hou, Yi [1 ]
机构：
[1] Natl Univ Def Technol, Sch Elect Sci & Engn, Changsha, Hunan, Peoples R China
来源：
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMPUTER VISION IN REMOTE SENSING | 2012年
关键词：
nonsubsampled contourlet transform; change detection; scale correlation; fusion; CFAR;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel change detection method for multi-temporal SAR images using nonsubsampled contourlet transform (NSCT) has been proposed. Firstly, we obtain the log-ratio map by comparing two co-registered SAR images with a ratio operator in a logarithmic scale. Secondly, the log-ratio map is decomposed into multiscale and multidirectional sub-images by NSCT, and the speckle noise in each sub-image is suppressed by scale correlation method. Finally, the changes in every sub-image are detected through a constant false alarm rate (CFAR) detector and the result map is derived according to an adaptive fusion strategy. Experimental results on simulated data and real airborne SAR imagery data both confirm the effectiveness of the proposed method.
引用
收藏
页码：377 / 382
页数：6
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