Matching SAR image to optical image using modified hausdorff distance and genetic algorithms

被引:0
|
作者
Mao, Haicen [1 ]
Yu, Qiuze [2 ]
Zhang, Tianxu [2 ]
机构
[1] Huazhong Inst Electroopt, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, Key Lab Educ Ministry Image Processing & Intellig, Wuhan 430074, Peoples R China
关键词
synthetic aperture radar (SAR) image; image matching; hausdorff distance; genetic algorithm; signal to noise ratio (SNTR);
D O I
10.1117/12.750623
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 algorithm for matching synthetic aperture radar (SAR) image to Optical image based on lineal feature using Hausdorff distance combined with genetic algorithm is proposed in this paper. A new method is presented to extract lineal feature from low signal to noise ratio (SNR) SAR image. Based on the edge image from SAR and Optical image, modified Hausdorff distance is adopted as a similarity measure because it is insensitive to noise. Genetic algorithm is used as searching strategy to achieve high computation speed for its inertial parallel. Experimental results using real SAR and Optical images demonstrate that the algorithm is robust, fast and can achieve high matching accuracy.
引用
收藏
页数:6
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