Interferometric synthetic aperture radar phase unwrapping based on sparse Markov random fields by graph cuts
Interferometric synthetic aperture radar phase unwrapping based on sparse Markov random fields by graph cuts
复制标题
基于稀疏马尔可夫随机场的图割干涉合成孔径雷达相位展开
DOI：
10.1117/1.jrs.12.015006
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发表时间：
2018-01
影响因子：
1.7
通讯作者：
Lin Hui
中科院分区：
文献类型：
--
作者：
Zhou Lifan;Chai Dengfeng;Xia Yu;Ma Peifeng;Lin Hui
抽象的。相位展开(PU)是从干涉合成孔径雷达(InSAR)数据中重建场景数字高程模型的关键步骤之一。众所周知，二维PU问题可以表示为马尔可夫随机场(MRF)的最大后验估计。然而，考虑到传统的马尔可夫随机场算法通常定义在矩形网格上，如果包裹的大部分数据被较大的低相干区或快速地形变化引起的噪声所主导，则该算法容易失败。提出了一种基于稀疏马尔可夫随机场的PU解决方案，将传统的马尔可夫随机场算法扩展到处理稀疏数据，允许对以高相位噪声为主的InSAR数据进行解缠。为了加速稀疏马尔可夫随机场的图割算法，我们设计了对偶初始图，并将它们合并得到Delaunay三角图，用来有效地最小化能量函数。通过对模拟数据和真实数据的实验，与其他已有算法相比，验证了该算法的有效性，该算法较少受大的低相干区或地形变化引起的去相关影响。
Abstract. Phase unwrapping (PU) is one of the key processes in reconstructing the digital elevation model of a scene from its interferometric synthetic aperture radar (InSAR) data. It is known that two-dimensional (2-D) PU problems can be formulated as maximum a posteriori estimation of Markov random fields (MRFs). However, considering that the traditional MRF algorithm is usually defined on a rectangular grid, it fails easily if large parts of the wrapped data are dominated by noise caused by large low-coherence area or rapid-topography variation. A PU solution based on sparse MRF is presented to extend the traditional MRF algorithm to deal with sparse data, which allows the unwrapping of InSAR data dominated by high phase noise. To speed up the graph cuts algorithm for sparse MRF, we designed dual elementary graphs and merged them to obtain the Delaunay triangle graph, which is used to minimize the energy function efficiently. The experiments on simulated and real data, compared with other existing algorithms, both confirm the effectiveness of the proposed MRF approach, which suffers less from decorrelation effects caused by large low-coherence area or rapid-topography variation.
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影响因子：
8.2
作者：
Ferretti, A;Prati, C;Rocca, F
通讯作者：
Rocca, F
影响因子：
8.2
作者：
Runpu Chen;Weidong Yu;Robert Wang;Gang Liu;Yunfeng Shao
通讯作者：
Runpu Chen;Weidong Yu;Robert Wang;Gang Liu;Yunfeng Shao
DOI：
10.1145/800061.808751
发表时间：
1983-12
期刊：
Proceedings of the fifteenth annual ACM symposium on Theory of computing
影响因子：
--
作者：
DiagramsWelson Jacometti
通讯作者：
DiagramsWelson Jacometti
影响因子：
10.6
作者：
Dias, JMB;Leitao, JMN
通讯作者：
Leitao, JMN
DOI：
10.1364/josaa.12.002393
发表时间：
1995-11
影响因子：
1.9
作者：
J. Marroquín;M. Rivera
通讯作者：
J. Marroquín;M. Rivera