SAR Images Change Detection Based on Comparison of Two-dimensional Probability Density Functions
Liu Yong-chun① Wang Guang-xue② Li Ping① Yan Xiao-peng①
①(National Key Laboratory of Mechatronic Engineer and Control, Beijing Institute of Technology, Beijing 100081, China ) ②(Department of Information Countermeasures, Air Force Early Warning Academy, Wuhan 430019, China)
Abstract：In this paper, the tradition change detection method based on local statistical feature is expanded to two-dimensional feature space, and a SAR image change detection method based on comparison of two-dimensional probability density functions is proposed. In this method, the values of adjacent pixels are combined to build two-dimensional observation vector. Then, in each temporal image, the Probability Density Function (PDF) of the vector is estimated by two-dimensional Gram-Charlier expansion. On the basis, change detection is fulfilled by computing the K-L divergence between the PDFs in different temporal images. Experiment results show that the proposed algorithm has better performance than the traditional method.
刘永春, 王广学, 栗苹, 闫晓鹏. 基于二维概率密度函数比较的SAR图像变化检测方法[J]. 电子与信息学报, 2015, 37(5): 1122-1127.
Liu Yong-Chun, Wang Guang-Xue, LI Ping, Yan Xiao-Peng. SAR Images Change Detection Based on Comparison of Two-dimensional Probability Density Functions. , 2015, 37(5): 1122-1127.
2015, Vol. 37 
