Abstract
In the last two decades, the use of synthetic aperture radar (SAR) for remote sensing purposes has significantly developed due to improvements in the quality and the availability of the images. Two powerful SAR techniques, namely, polarimetry and interferometry, have further increased the range of applications of the sensed data. Using polarimetry, geometrical properties and geophysical parameters, such as shape, roughness, texture, and moisture content, can be retrieved with considerable accuracy, while interferometric information may be used to extract vertical information with accuracy less than 1 cm. In this paper, the potential of using joint polarimetry and interferometry techniques in SAR data (PolInSAR) for the purpose of SAR image classification is investigated. To achieve this goal, we extend a covariance symmetry detection framework to the PolInSAR scenario. The proposed approach will be shown to be able to exploit the peculiar structures of the covariance matrices of PolInSAR images to discriminate structures within the image. Results using real-SAR data are presented to validate the effectiveness of the proposed approach.
Highlights
P OLARIMETRIC interferometry is a recent technique, [1] which uses two spatially shifted polarimetric antennas allowing the measurement of the coherence associated with the various polarimetric channels as well as the height of the polarimetric phase centers
We have extended a recent framework for detecting covariance symmetries to the PolInSAR data; the formulation of detecting covariance symmetries within the PolSAR data has been adapted to PolInSAR in order to detect the symmetry and its associated interferometric information, by using the cross-covariance matrix instead of the cocovariance
The procedure considers the generalized information criterion (GIC) approach in order to deal with the multiple hypothesis testing problem, since that GIC provides good results
Summary
P OLARIMETRIC interferometry is a recent technique, [1] which uses two spatially shifted polarimetric antennas allowing the measurement of the coherence associated with the various polarimetric channels as well as the height of the polarimetric phase centers. The purpose of this paper is to extend the framework developed in [9] for the detection of covariance symmetries in polarimetry and interferometry techniques in SAR data (PolInSAR). The proposed analytical framework differs from that of [9], as it accounts for peculiar characteristics of the PolInSAR covariance matrices as well as thanks to its capabilities to provide a novel tool for advanced remote sensing applications An example of the latter consists in integrating the proposed approach in an enhanced H-A-α [10], [11] PolInSAR decomposition in order to extract different classes containing both the symmetry and elevation information.
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