相关系数图分类及其在干涉SAR二维相位展开中的应用
Coherence MAP Classification and Its Application in Two-Dimensional Phase Unwrapping
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摘要: 二维相位展开是干涉SAR数据处理中的关键步骤。该文在讨论干涉SAR相关系数图分类与二维相位展开之间关系的基础上，将相关系数图分类应用于干涉SAR二维相位展开。提出了基于K-均值-Markov随机场的干涉SAR相关系数图组合分类算法。在相位展开时对特定类别的区域作相应的处理，避免了不含有效相位区域的相位误差在相位展开过程中的传播。实验结果证实了该方法的有效性。Abstract: Based on the analyzing of the relation between interferoinetric SAR coherence map classification and two-dimensional phase unwrapping, coherence map classification is applied in two-dimensional phase unwrapping. A K-mean and Markov random field combined classification algorithm is presented for the coherence map classification. The classified coherence map is used to confine the propagation of the local phase errors of low coherence! regions during the two-dimensional phase unwrapping. The experiments on airborne X-band InSAR data show the validity of this approach.
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