Spatially adaptive despeckling of SAR image using bivariate thresholding in directionlet domain

Abstract

A novel spatially adaptive despeckling algorithm is presented for a synthetic aperture radar (SAR) image by taking into account the statistical interscale dependency of the directionlet transform (DT) coefficients. The DT is first computed along the dominant directions of the spatially segmented image. The signal and the noise coefficients are modelled using bivariate distributions which take into account the statistical dependence between the adjacent scale coefficients. The nonlinear threshold functions derived from the models employing a maximum a posteriori estimator are then used for estimating the noise-free coefficients. The experimental results show that the proposed method outperforms similar methods in terms of numerical and perceptual quality.