Polarimetric SAR Change Detection With the Complex Hotelling-Lawley Trace Statistic

In this paper, we propose a new test statistic for unsupervised change detection in polarimetric radar images. We work with multilook complex covariance matrix data, whose underlying model is assumed to be the scaled complex Wishart distribution. We use the complex-kind Hotelling-Lawley trace (HLT)...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2016-07, Vol.54 (7), p.3953-3966
Main Authors: Akbari, Vahid, Anfinsen, Stian N., Doulgeris, Anthony P., Eltoft, Torbjorn, Moser, Gabriele, Serpico, Sebastiano B.
Format: Article
Language:English
Subjects:
Approximation
Change detection
complex Wishart distribution
Computational modeling
Covariance matrices
Detectors
Estimation
Fisher-Snedecor (FS) distribution
Fisher-Snedecor distribution
Geofag: 450
Hotelling-Lawley trace (HLT) statistic
Hotelling-Lawley trace statistic
Likelihood ratio
likelihood ratio test (LRT) statistic
likelihood ratio test statistic
Matematikk og Naturvitenskap: 400
Object oriented modeling
Optical sensors
polarimetry
Similarity
Simulation
Statistical tests
Statistics
Synthetic aperture radar
synthetic aperture radar (SAR)
VDP
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Summary:In this paper, we propose a new test statistic for unsupervised change detection in polarimetric radar images. We work with multilook complex covariance matrix data, whose underlying model is assumed to be the scaled complex Wishart distribution. We use the complex-kind Hotelling-Lawley trace (HLT) statistic for measuring the similarity of two covariance matrices. The distribution of the HLT statistic is approximated by a Fisher-Snedecor distribution, which is used to define the significance level of a false alarm rate regulated change detector. Experiments on simulated and real PolSAR data sets demonstrate that the proposed change detection method gives detection rates and error rates that are comparable with the generalized likelihood ratio test.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2016.2532320