Generalized minimum-error thresholding for unsupervised change detection from multilook polarimetric SAR data

In this paper, we propose a robust unsupervised change detection algorithm for multilook polarimetric synthetic aperture radar (PolSAR) data. The Hotelling-Lawley trace (HLT) statistic is used as a test statistic to measure the similarity of two covariance matrices. The generalized Kittler and Illingworth (K&I) minimum-error thresholding algorithm based on the generalized gamma function is then applied on the test statistic image to accurately discriminate changed and unchanged areas. Experiment on real PolSAR data set demonstrates the accuracy of the proposed change detection method.

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