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中国物理学会期刊

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

CSTR: 32037.14.aps.56.4565

Maximum a posteriori filtering for synthetic aperture radar images based on heavy-tailed Rayleigh distribution of speckle

CSTR: 32037.14.aps.56.4565
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  • 为了反映合成孔径雷达图像中斑点噪声尖峰厚尾的统计特征,使用拖尾Rayleigh分布来描述斑点噪声.基于Gamma先验分布和斑点噪声的拖尾Rayleigh分布,推导出了合成孔径雷达图像的最大后验概率滤波方程,并给出了它在特定特征参数时的解析形式.使用Mellin变换从观察图像估计拖尾Rayleigh分布的未知参数.给出了在斑点噪声的拖尾Rayleigh分布下的最大后验概率降噪试验和量化指标.为了消除滑动窗大小和噪声强度对降噪结果的影响,给出了降噪能力随滑动窗大小和噪声方差的动态变化关系.结果表明,拖尾Ray

     

    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.

     

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