نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Synthetic Aperture Radar (SAR) images have many applications in different fields. But, the existence of multiplicative noise called speckle is a problem in processing SAR images. So, speckle suppression is an essential step in processing SAR images. In this paper, a novel Bayesian wavelet domain speckle suppression method is proposed that is based on joint modeling. In the proposed method, first logarithm and then wavelet transform are applied to the SAR images. Normal Inverse Gaussian (NIG) distribution is used for statistical modeling of wavelet coefficients. Due to the importance of precise statistical modeling and the existence of dependency between wavelet coefficients, proposed method captures the dependencies of wavelet coefficients using joint modeling. Then, based on using the proposed model, a minimum mean square error (MMSE) estimator is designed to denoise SAR images. Experimental results using synthetic and real SAR images demonstrate the efficiency of the proposed method.
کلیدواژهها English
