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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Rayleigh分布尖峰厚尾的特征符合斑点噪声的真实统计特性,因此与Rayleigh分布以及Kuan滤波相比,基于斑点噪声的拖尾Rayleigh分布的最大后验概率滤波具有较强的降噪能力.
In order to reflect the statistical characteristics of speckle spikes and thick tails in synthetic aperture radar images, the trailing Rayleigh distribution is used to describe speckle noise.Based on the priori distribution of Gamma and the trailing Rayleigh distribution of speckle noise, the maximum of the synthetic aperture radar image is deduced The probability filtering equation is tested and its analytical form is given when it is in a certain characteristic parameter.Using the Mellin transform to estimate the unknown parameters of the trailing Rayleigh distribution from the observed images, the maximum a-posteriori under the Rayleigh distribution of speckle noise Probability of noise reduction test and quantitative indicators.In order to eliminate the impact of sliding window size and noise intensity on the noise reduction results, the relationship between the noise reduction ability and sliding window size and noise variance is given.The results show that the tailing Rayleigh distribution peak thickness The tail features are in line with the true statistics of speckle noise. Therefore, the maximum a posteriori probability filter based on speckle-noise-based smear-based Rayleigh distribution has better noise reduction than Rayleigh distribution and Kuan filtering.