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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >SAR Image Despeckling Based on Local Homogeneous-Region Segmentation by Using Pixel-Relativity Measurement
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SAR Image Despeckling Based on Local Homogeneous-Region Segmentation by Using Pixel-Relativity Measurement

机译：像素相关性测量的基于局部均匀区域分割的SAR图像去斑

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摘要

This paper provides a novel pointwise-adaptive speckle filter based on local homogeneous-region segmentation with pixel-relativity measurement. A ratio distance is proposed to measure the distance between two speckled-image patches. The theoretical proofs indicate that the ratio distance is valid for multiplicative speckle, while the traditional Euclidean distance failed in this case. The probability density function of the ratio distance is deduced to map the distance into a relativity value. This new relativity-measurement method is free of parameter setting and more functional compared with the Gaussian kernel-projection-based ones. The new measurement method is successfully applied to segment a local shape-adaptive homogeneous region for each pixel, and a simplified strategy for the segmentation implementation is given in this paper. After segmentation, the maximum likelihood rule is introduced to estimate the true signal within every homogeneous region. A novel evaluation metric of edge-preservation degree based on ratio of average is also provided for more precise quantitative assessment. The visual and numerical experimental results show that the proposed filter outperforms the existing state-of-the-art despeckling filters.
机译：本文提供了一种基于局部均一区域分割和像素相关性测量的新型逐点自适应散斑滤波器。提出了比率距离以测量两个斑点图像斑块之间的距离。理论证明表明，比率距离对于乘性散斑是有效的，而传统的欧几里得距离在这种情况下是失败的。推导比率距离的概率密度函数，以将距离映射为相对值。与基于高斯核投影的方法相比，这种新的相对性测量方法无需参数设置，但功能更多。该新的测量方法已成功地应用于对每个像素的局部形状自适应均匀区域进行分割，并给出了一种简化的分割策略。在分割之后，引入最大似然规则以估计每个同质区域内的真实信号。还提供了一种基于平均比率的边缘保存度的新评​​估指标，以进行更精确的定量评估。视觉和数值实验结果表明，所提出的滤波器优于现有的最新去斑滤波器。

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