Despeckling SAR images in the lapped transform domain

Abstract

In this paper, a novel lapped transform (LT) based approach to SAR image despeckling is introduced. It is shown that LT coefficients of the log transformed, noise free SAR images, obey Generalized Gaussian distribution. The proposed method uses a Bayesian minimum mean square error (MMSE) estimator which is based on modeling the global distribution of the rearranged LT coefficients in a subband using Generalized Gaussian distribution. Finally the proposed algorithm is implemented in cycle spinning mode to compensate for the lack of translation invariance property of LT. Experiments are carried out using synthetically speckled natural and SAR images. The proposed Bayesian based technique in LT based framework, when compared with several existing despeckling techniques, yields very good despeckling results while preserving the important details and textural information of the scene.