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A CFAR Algorithm for Layover and Shadow Detection in InSAR Images Based on Kernel Density Estimation

机译:基于核密度估计的InSAR图像中的阴影和阴影CFAR算法

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In this paper, a novel CFAR algorithm for detecting layover and shadow areas in Interferometric synthetic aperture radar (InSAR) images is proposed. Firstly, the probability density function (PDF) of the square root amplitude of InSAR image is estimated by the kernel density estimation. Then, a CFAR algorithm combining with the morphological method for detecting both layover and shadow is presented. Finally, the proposed algorithm is evaluated on a real InSAR image obtained by TerraSAR-X system. The experimental results have validated the effectiveness of the proposed method.
机译:本文提出了一种新颖的CFAR算法,用于检测干涉式合成孔径雷达(InSAR)图像中的覆盖区和阴影区。首先,通过核密度估计来估计InSAR图像平方根振幅的概率密度函数(PDF)。然后,提出了一种结合形态学方法的CFAR算法,用于同时检测覆盖和阴影。最后,在TerraSAR-X系统获得的真实InSAR图像上对提出的算法进行了评估。实验结果验证了该方法的有效性。

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