A Quality-Guided and Local Minimum Discontinuity Based Phase Unwrapping Algorithm for InSAR/InSAS Interferograms
A Quality-Guided and Local Minimum Discontinuity Based Phase Unwrapping Algorithm for InSAR/InSAS Interferograms
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DOI：
10.1109/lgrs.2013.2252880
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发表时间：
2014
影响因子：
4.8
通讯作者：
Heping Zhong;Jinsong Tang;Sen Zhang;Xuebo Zhang
中科院分区：
文献类型：
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作者：
Heping Zhong;Jinsong Tang;Sen Zhang;Xuebo Zhang
相位解缠是利用干涉合成孔径雷达（干涉合成孔径雷达）或干涉合成孔径声纳（InSAS）数据重建场景数字高程模型的关键问题之一。本文提出了一种基于局部最小不连续性的质量引导相位解缠算法，该算法通过局部最小不连续性优化提高了低质量区域的解缠精度，同时保持了较高的效率。新算法可分为两步。首先，对原始包裹后的相位图进行质量引导的相位解包裹算法，该算法有助于快速去除包裹操作引起的所有不连续性，但容易将解包裹误差扩散到低质量区域。其次，根据初始解缠结果的质量图将其划分为高质量区域和低质量区域，并对初始解缠结果的低质量区域进行最小不连续性优化处理，从而去除剩余的改进环（定义为正跳数多于负跳数的环）。这防止了展开错误从低质量区域传播到高质量区域，并且通过将优化位置限制在低质量区域中来加速优化过程。通过对干涉合成孔径雷达和真实的InSAS数据的测试，验证了该算法的有效性和准确性。
Phase unwrapping is one of the key problems in reconstructing the digital elevation model of a scene from its interferometric synthetic aperture radar (InSAR) or interferometric synthetic aperture sonar (InSAS) data. In this letter, we propose a quality-guided and local minimum discontinuity based phase unwrapping algorithm, which enhances the precision of the unwrapped result by local minimum discontinuity optimization in low quality areas, and still keeps a high efficiency. The new algorithm can be divided into two steps. Firstly, the quality-guided phase unwrapping algorithm is performed on the original wrapped phase image, which helps to remove all the discontinuities caused by the wrapping operation quickly, but tends to spread the unwrapped errors in low quality areas. Secondly, the initial unwrapped result is divided into high and low quality areas according to its quality map, and the minimum discontinuity optimization process is performed in the low quality areas of the initial unwrapped result, which helps to remove the remaining improving loops defined as a loop with more positive jumps than negative ones. This prevents the unwrapped errors spreading from low quality areas to high quality areas and accelerates the optimization process by restricting the optimization place in low quality areas. Tests performed on InSAR and real InSAS data confirm the accuracy and efficiency of the proposed algorithm.