Three-Component Model-Based Decomposition for Polarimetric SAR Data
Three-Component Model-Based Decomposition for Polarimetric SAR Data
复制标题
基于三分量模型的偏振SAR数据分解
DOI：
10.1109/tgrs.2010.2041242
复制
发表时间：
2010-06-01
影响因子：
8.2
通讯作者：
Yang, Jian
中科院分区：
文献类型：
--
作者：
An, Wentao;Cui, Yi;Yang, Jian
提出了一种改进的极化合成孔径雷达（SAR）数据三分量分解方法。分析了Freeman分解中出现负幂的原因，并提出了相应的改进方法。首先，在相干矩阵分解成三个散射分量之前，对相干矩阵进行去取向处理。然后，具有最大极化熵的相干矩阵，即，的单位矩阵，被用来作为新的体积散射模型，而不是原来的一个采用的弗里曼分解。功率约束也被添加到建议的三分量分解。在实验中使用了在德国Oberpfaffenhofen地区获得的E-SAR极化数据。实验结果表明，该方法能有效地去除负幂像素，证明了该模型的有效性。
An improved three-component decomposition for polarimetric synthetic aperture radar (SAR) data is proposed in this paper. The reasons for the emergence of negative powers in the Freeman decomposition have been analyzed, and three corresponding improvements are included in the proposed method. First, the deorientation process is applied to the coherency matrix before it is decomposed into three scattering components. Then, the coherency matrix with the maximal polarimetric entropy, i.e., the unit matrix, is used as the new volume-scattering model instead of the original one adopted in the Freeman decomposition. A power constraint is also added to the proposed three-component decomposition. The E-SAR polarimetric data acquired over the Oberpfaffenhofen area in Germany are applied in the experiment. The results show that the pixels with negative powers are totally eliminated by the proposed decomposition, demonstrating the effectiveness of the new model.