Maximum a posteriori filtering for synthetic aperture radar images based on heavy-tailed Rayleigh distribution of speckle
基于斑点噪声的拖尾Rayleigh分布的合成孔径雷达图像最大后验概率降噪

In order to reflect the statistics of high peak and heavy tail,speckle in synthetic aperture radar images is modeled as heavy-tailed Rayleigh distribution.First,based on Gamma prior distribution and heavy-tailed Rayleigh distribution of speckle,the maximum a posteriori filtering equation is proposed and its analytical form is provided in given characteristic parameter.Second,parameters of heavy-tailed Rayleigh distribution are estimated from the observed image using Mellin transformation.Last,maximum a posteriori de-speckling experiments and their quantitative measures are given.In order to eliminate the influence of window size and noise intensity on de-speckling results,dynamic relations of the de-speckling capability to noise variance and window size are suggested respectively.Results demonstrate that the heavy-tailed Rayleigh distribution accords with the real statistics of speckle,so the maximum a posteriori filter in heavy-tailed Rayleigh distribution of speckle has higher capability of noise reduction compared to the one in Rayleigh distribution of speckle and the Kuan filter.