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

被引:15
|
作者
Bouhlel, Nizar [1 ,2 ]
Akbari, Vahid [3 ]
Meric, Stephane [4 ]
机构
[1] CentraleSupelec, IETR, Team SCEE, F-35042 Rennes, France
[2] Inst Agro, Stat & Comp Sci Dept, F-49045 Angers, France
[3] Univ Stirling, Dept Comp Sci & Math, Stirling 9037, Scotland
[4] IETR, Dept Image & Remote Sensing, UMR CNRS 6164, F-35708 Rennes, France
关键词
Change detection; complex Wishart distribution determinant ratio test (DRT); Hotelling-Lawley trace (HLT); likelihood ratio test (LRT); multilook polarimetric synthetic; aperture radar (SAR) data; Wilks's lambda of the second kind distribution; UNSUPERVISED CHANGE DETECTION; PRODUCTS;
D O I
10.1109/TGRS.2020.3043517
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
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.
引用
收藏
页数:15
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