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| 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) |
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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.
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Received: 01 September 2014
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Corresponding Authors:
Wang Guang-xue
E-mail: wgxradar@163.com
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2015, Vol. 37 
