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Change Detection in Multilook Polarimetric SAR Imagery With Determinant Ratio Test Statistic

Abstract : In this article, we propose a determinant ratio test (DRT) statistic to measure the similarity of two covariance matrices for unsupervised change detection in polarimetric radar images. The multilook complex covariance matrix is assumed to follow a scaled complex Wishart distribution. In doing so, we provide the distribution of the DRT statistic that is exactly Wilks's lambda of the second kind distribution, with density expressed in terms of Meijer G-functions. Due to this distribution, the constant false alarm rate (CFAR) algorithm is derived in order to achieve the required performance. More specifically, a threshold is provided by the CFAR to apply to the DRT statistic producing a binary change map. Finally, simulated and real multilook polarimetric SAR (PolSAR) data are employed to assess the performance of the method and is compared with the Hotelling-Lawley trace (HLT) statistic and the likelihood ratio test (LRT) statistic.
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Contributor : Laurent Jonchère Connect in order to contact the contributor
Submitted on : Wednesday, March 31, 2021 - 4:52:58 PM
Last modification on : Friday, October 22, 2021 - 3:04:09 AM
Long-term archiving on: : Thursday, July 1, 2021 - 6:58:43 PM


Bouhlel et al-2020-Change Dete...
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N. Bouhlel, V. Akbari, S. Meric. Change Detection in Multilook Polarimetric SAR Imagery With Determinant Ratio Test Statistic. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2020, pp.1-15. ⟨10.1109/TGRS.2020.3043517⟩. ⟨hal-03164088⟩



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