Despeckling of synthetic aperture radar images in the contourlet domain using the alpha-stable distribution

Speckle reduction has been a prerequisite for many SAR image processing tasks. This work presents a new approach for despeckling of SAR images in the contourlet domain using the alpha-stable distribution. It is shown that the alpha-stable distribution provides a good fit for the contourlet coefficients of an image, since it can capture the large peak and heavy tails of the distribution of the empirical data. This model is then exploited in a Bayesian maximum a posteriori estimator to restore the noise-free contourlet coefficients. The performance of the proposed despeckling method is evaluated using synthetically-speckled and real SAR images. Simulations are carried out using synthetically speckled images to investigate the performance of the proposed method, and compare it with that of some of the existing methods. The experimental results show that the proposed method can provide better preservation of the edges and can yield better visual quality as compared to some of the existing methods.