Change Detection in Multilook Polarimetric SAR Imagery With Determinant Ratio Test Statistic
Résumé
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.
Mots clés
Wilks's lambda of the second kind distribution.
Synthetic aperture radar
Speckle
Change detection
complex Wishart distribution
Covariance matrices
determinant ratio test (DRT)
Hotelling-Lawley trace (HLT)
Light rail systems
likelihood ratio test (LRT)
multilook polarimetric synthetic aperture radar (SAR) data
Radar polarimetry
Random variables
Scattering
Domaines
Sciences de l'ingénieur [physics]
Fichier principal
Bouhlel et al-2020-Change Detection in Multilook Polarimetric SAR Imagery With Determinant Ratio.pdf (9.46 Mo)
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