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Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Change Detection in Multilook Polarimetric SAR Imagery With Determinant Ratio Test Statistic
Author(s): Bouhlel, Nizar
Akbari, Vahid
Meric, Stephane
Keywords: Covariance matrices
Light rail systems
Random variables
Synthetic aperture radar
Radar polarimetry
Issue Date: 29-Dec-2020
Date Deposited: 4-Mar-2021
Citation: Bouhlel N, Akbari V & Meric S (2020) Change Detection in Multilook Polarimetric SAR Imagery With Determinant Ratio Test Statistic. IEEE Transactions on Geoscience and Remote Sensing.
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.
DOI Link: 10.1109/TGRS.2020.3043517
Rights: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Notes: Output Status: Forthcoming/Available Online

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