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Scattering-model-based speckle filtering of polarimetric SAR data

机译:基于散射模型的极化SAR数据斑点滤波

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摘要

A new concept in polarimetric synthetic aperture radar (POLSAR) speckle filtering that preserves the dominant scattering mechanism of each pixel is proposed in this paper. The basic principle is to select pixels of the same scattering characteristics to be included in the filtering process. To achieve this, the algorithm first applies the Freeman and Durden decomposition to separate pixels into three dominant scattering categories: surface, double bounce, and volume, and then unsupervised classification is applied. Speckle filtering is performed using the classification map as a mask. A single-look or multilook pixel centered in a 9 /spl times/ 9 window is filtered by including only pixels in the same and two neighboring classes from the same scattering category. This filter is effective in speckle reduction, while perfectly preserving strong point target signatures, and retains edges, linear, and curved features in the POLSAR data. The effect of speckle filtering on scattering characteristics, such as entropy, anisotropy, and alpha angle, will be discussed.
机译:提出了极化合成孔径雷达(POLSAR)斑点滤波的新概念,该概念保留了每个像素的主要散射机制。基本原理是选择具有相同散射特性的像素以包括在滤波过程中。为此,该算法首先应用Freeman和Durden分解将像素分为三个主要的散射类别:表面,双反射和体积,然后应用无监督分类。使用分类图作为蒙版执行斑点过滤。通过仅包含9个/ spl次/ 9窗口中的单眼或多眼像素,可以只包含相同散射类别中相同和两个相邻类别中的像素。该过滤器可有效减少斑点,同时完美保留强点目标特征,并在POLSAR数据中保留边缘,线性和弯曲特征。将讨论斑点滤波对散射特性(例如熵,各向异性和α角)的影响。

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