Directionlet-Based Bayesian Filter for SAR Image Despeckling

Abstract Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the radar coherent wave. In this paper, we introduce a new SAR despeckling method based on directionlet transform using Bayesian MAP estimator. The directionlet coefficients of the logarithmically transformed reflectance image and the speckle image are modeled Cauchy PDF and additive Gaussian distribution, respectively. Then, we exploit this as a priori information to design a maximum a posterior (MAP) estimator. A new method for estimating the dispersion parameter of Cauchy distribution is also presented. Experiment results, carried out on both synthetic speckled image and real SAR image, show that the proposed scheme removes noise from SAR images more efficiently.