Abstract
<p>In this paper, we present a novel approach for joint decorrelation<br />and despeckling of synthetic aperture radar (SAR) imagery. An iterative<br />maximum a posterior estimation is performed to obtain the<br />correlation and speckle-free SAR data, which incorporates a correlation<br />model which realistically explores the physical correlated<br />process of speckle noise on signal in SAR imaging. The correlation<br />model is determined automatically via Bayesian estimation in the<br />log-Fourier domain and patch-wise computation is used to account<br />for spatial nonstationarities existing in SAR data. The proposed<br />approach is compared to a state-of-the-art despeckling technique<br />using both simulated and real SAR data. Experimental results illustrate<br />its improvement in preserving the structural detail, especially<br />the sharpness of the edges, when suppressing speckle noise.</p>
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