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The Hotelling-Lawley trace statistic for change detection in polarimetric SAR data under the complex Wishart distribution

机译:复杂Wishart分布下用于极化SAR数据变化检测的Hotelling-Lawley跟踪统计量

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In this paper we propose a new test statistic for unsupervised change detection in polarimetric synthetic aperture radar (Pol-SAR) data. We work with multilook complex (MLC) covariance matrix data, whose underlying model is assumed to be the scaled complex Wishart distribution. We use the complex kind Hotelling-Lawley (HL) trace statistic for measuring the similarity of two covariance matrices. The sampling distribution of the HL trace is approximated by a Fisher-Snedecor distribution, which is used to define the significance level of a constant false alarm rate change detector. The performance of the proposed method is tested on simulated and real PolSAR data sets and compared to the likelihood ratio test statistic.
机译:在本文中,我们为极化合成孔径雷达(Pol-SAR)数据中的无监督变化检测提出了一种新的测试统计量。我们处理多视复杂(MLC)协方差矩阵数据,其基础模型被假定为缩放后的复杂Wishart分布。我们使用复杂种类的Hotelling-Lawley(HL)跟踪统计量来测量两个协方差矩阵的相似性。 HL跟踪的采样分布通过Fisher-Snedecor分布进行近似,该分布用于定义恒定误报率变化检测器的显着性水平。在模拟和真实的PolSAR数据集上测试了该方法的性能,并与似然比测试统计数据进行了比较。

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