Test Statistics for Reflection Symmetry: Applications to Quad-Polarimetric SAR Data for Detection of Man-Made Structures

Abstract

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 ⟨ShhS * hv ⟩, ⟨SvvS * hv ⟩, 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.

Corrections to “Test Statistics for Reflection Symmetry: Applications to Quad-Polarimetric SAR Data for Detection of Man-Made Structures”

“…In [1] there is a typo in the expression for f immediately below Equation (8) on page 2879. The expression should be…”

A Comparison of CFAR Object Detection Algorithms for Iceberg Identification in L- and C-band SAR Imagery of the Labrador Sea

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Rotation of Polarimetric SAR Covariance Matrices

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