A robust change detector for multilook polarimetric synthetic aperture radar data

Abstract

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 is then applied on the test statistic image to accurately discriminates changed and unchanged areas. The algorithm, tested on real PolSAR images, provides satisfactory results.