SAR Image Despeckling Based on Generalized Gamma Distributio
Yuan Zhan · Fire Control and Command Control · 2013
In this paper,the recently introduced generalized Gamma distribution is utilized to model the statistical properties of synthetic aperture radar(SAR) imagery,and a new adaptive despeckling algorithm is accordingly proposed.The backscattering cross-section of distributed targets is estimated using maximum a posteriori criterion in the framework of Bayesian theory.The unknown model parameters are estimated by means of method of log-cumulants relying on the Mellin transform.Experimental results show that the proposed despeckling algorithm can efficiently removes speckle noise from SAR images.