Journal article · Ahead of Print article
Test statistics for reflection symmetry, applications to quad-polarimetric SAR data for detection of man-made structures
Department of Space Research and Technology, Technical University of Denmark1
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Management, Department of Space Research and Technology, Technical University of Denmark4
In polarimetric Synthetic Aperture Radar (SAR) images, speckle is removed by multilooking and the local covariance matrix is the main parameter of interest. In the covariance matrix from a backscatter with reflection symmetry, the terms ⟩, , and their complex conjugates are 0. The backscatter from natural covers, such as fields and forested areas is typically reflection symmetric, as these four elements have near zero values.
The backscatter from urban areas and man-made structures is substantially different, and the backscatter from buildings not aligned with the radar line of sight usually does not have reflection symmetry. A novel block-diagonality test statistic for reflection symmetry with a Constant False Alarm Rate property is proposed.
It is compared to an approximate test built on a change detection test statistic for Wishart distributed covariance matrices. Their use on quad-polarimetric data in different situations shows their high potential for manmade structure detection. Applied after an orientation correction of the covariance matrices, these test statistics highlight with high contrast buildings and urban areas.
We also apply this test for ship detection at sea, and show that while the results are unconvincing at X-band, it can also be applied at longer wavelengths such as L-band.
Language: | English |
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Publisher: | IEEE |
Year: | 2022 |
Pages: | 2877-2890 |
ISSN: | 21511535 and 19391404 |
Types: | Journal article and Ahead of Print article |
DOI: | 10.1109/JSTARS.2022.3162670 |
ORCIDs: | Connetable, Paul Jacques , Nielsen, Allan Aasbjerg , Skriver, Henning and Conradsen, Knut |