Hierarchical segmentation of Polarimetric SAR images using heterogeneous clutter models
Hierarchical segmentation of Polarimetric SAR images using heterogeneous clutter models
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DOI：
10.1109/igarss.2009.5418271
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发表时间：
2009-07
期刊：
影响因子：
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通讯作者：
L. Bombrun;Jean-Marie Beaulieu;Gabriel Vasile;J. Ovarlez;F. Pascal;M. Gay
中科院分区：
文献类型：
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作者：
L. Bombrun;Jean-Marie Beaulieu;Gabriel Vasile;J. Ovarlez;F. Pascal;M. Gay
在本文中，引入了异质的混乱模型来描述偏光合成孔径雷达（POLSAR）数据。根据球形不变的随机向量（SIRV）估计方案，提取标量纹理参数和归一化协方差矩阵。如果纹理参数由Fisher PDF建模，则观察到的目标散射向量遵循Kummeru PDF。然后，该PDF以分层分割算法实现。分割结果显示在L和}频段的高分辨率POLSAR数据上。
In this paper, heterogeneous clutter models are introduced to describe Polarimetric Synthetic Aperture Radar (PolSAR) data. Based on the Spherically Invariant Random Vectors (SIRV) estimation scheme, the scalar texture parameter and the normalized covariance matrix are extracted. If the texture parameter is modeled by a Fisher PDF, the observed target scattering vector follows a KummerU PDF. Then, this PDF is implemented in a hierarchical segmentation algorithm. Segmentation results are shown on high resolution PolSAR data at L and}band.