Change Detection with SAR Images Based on Radon Transform and Jeffrey Divergence
Zheng Jin①②③ You Hong-jian①②
①(Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China) ②(Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics,
Chinese Academy of Sciences, Beijing 100190, China) ③(Graduate University, Chinese Academy of Sciences, Beijing 100049, China)
Abstract：Focusing on the change detection with multitemporal Synthetic Aperture Radar (SAR) images, this paper presents a new approach based on the comparison of the density of the projections produced by Radon transform. The projections include the structure information, which helps when the local statistical distribution does not change. Edgeworth approach is used to fit the statistical distribution model of the projections. Jeffrey divergence is proposed as a measurement of the difference between two densities for that it is numerically stable and robust with respect to noise. This approach is demonstrated feasible according to the processing test using real satellite SAR images.
郑 瑾, 尤红建. 基于Radon 变换和Jeffrey 散度的SAR 图像变化检测方法[J]. 雷达学报, 2012, 1(2): 182-189.
Zheng Jin, You Hong-jian. Change Detection with SAR Images Based on Radon Transform and Jeffrey Divergence. JOURNAL OF RADARS, 2012, 1(2): 182-189.
