Open AccessMaximum a posteriori filtering for synthetic aperture radar images based on heavy-tailed Rayleigh distribution of speckle
Author(s) -
Zengguo Sun,
Chongzhao Han
Publication year - 2007
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.56.4565
Subject(s) - rayleigh distribution , speckle pattern , maximum a posteriori estimation , speckle noise , rayleigh scattering , synthetic aperture radar , noise (video) , k distribution , filter (signal processing) , distribution (mathematics) , optics , physics , mathematics , probability distribution , statistics , computer science , mathematical analysis , maximum likelihood , image (mathematics) , artificial intelligence , computer vision
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.