Abstract
In this work, we extended a procedure for the spatial decorrelation of fully-developed speckle, originally developed for single-polarization SAR data, to fully-polarimetric SAR data. The spatial correlation of the noise depends on the tapering window in the Fourier domain used by the SAR processor to avoid defocusing of targets caused by Gibbs effects. Since each polarimetric channel is focused independently of the others, the noise-whitening procedure can be performed applying the decorrelation stage to each channel separately. Equivalently, the noise-whitening stage is applied to each element of the scattering matrix before any multilooking operation, either coherent or not, is performed. In order to evaluate the impact of a spatial decorrelation of the noise on the performance of polarimetric despeckling filters, we make use of simulated PolSAR data, having user-defined polarimetric features. We optionally introduce a spatial correlation of the noise in the simulated complex data by means of a 2D separable Hamming window in the Fourier domain. Then, we remove such a correlation by using the whitening procedure and compare the accuracy of both despeckling and polarimetric features estimation for the three following cases: uncorrelated, correlated, and decorrelated images. Simulation results showed a steady improvement of performance scores, most notably the equivalent number of looks (ENL), which increased after decorrelation and closely attained the value of the uncorrelated case. Besides ENL, the benefits of the noise decorrelation hold also for polarimetric features, whose estimation accuracy is diminished by the correlation. Also, the trends of simulations were confirmed by qualitative results of experiments carried out on a true Radarsat-2 image.
Highlights
Multipolarization synthetic aperture radar, known as polarimetric synthetic aperture radar (PolSAR), makes use of polarization diversity of electromagnetic waves to improve the characterization, both geometrical and geophysical, of the surface being imaged
We investigated the impact of a decorrelation of the noise on despeckling and information extraction from PolSAR data
The decrement in polarimetric features-estimation accuracy induced by correlation is moderate, yet non-negligible, and might diminish the performance attainable by analysis methods using geo/biophysical modeling based on estimation of polarimetric features
Summary
Multipolarization synthetic aperture radar, known as PolSAR, makes use of polarization diversity of electromagnetic waves to improve the characterization, both geometrical and geophysical, of the surface being imaged. Regardless of the polarization configuration, the main drawback of SAR images is the presence of speckle, a signal-dependent granular noise inherent of all active coherent imaging systems, which visually degrades the appearance of images and severely diminishes the performance attainable by automatic information-extraction tools. The topic of speckle filtering, that is, despeckling of SAR images has received considerable attention over time and many algorithms have been proposed during the last four decades [2]. Fully-polarimetric SAR systems measure the complex scattering matrix, S, that links the transmitted and incident electromagnetic field to the backscattered electromagnetic field received by the radar, at every pixel position. In case of reciprocal backscattering, the cross-polar terms can be equalized [29], and the scattering matrix (1) may be expressed as a complex vector that may take two different forms: √ T.
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