A New Effective Approach for Enhancement of SAR Images Based on Extraction of Interscale Dependencies in the Wavelet Domain

Despite the wide application of SAR images in lineaments extraction, DEM generation and displacements determination, their radiometric quality and interpretability is degraded due to the presence of a multiplicative noise called speckle. Therefore, the enhancement of SAR images is an important step before using them in any application. In this paper, a new image enhancement method tailored to SAR images is proposed. In this method, the logarithmically transformed SAR image is decomposed using the dual-tree complex wavelet transform (DTCWT).In order to effectively extract the wavelet interscale dependencies, the signal component of wavelet coefficients is modeled with an isotropic stable distribution, while the noise component is approximated using an isotropic Gaussian model. A bivariate Bayesian estimator is then designed to effectively remove speckle from noisy coefficients in the complex wavelet domain. Both quantitative and qualitative comparisons of the proposed method with new speckle reduction methods, demonstrate its higher performance in speckle reduction from SAR images