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A two-dimensional region growing least squares phase unwrapping algorithm for interferometric SAR processing

机译:用于干涉SAR的二维区域增长最小二乘相位展开算法

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This paper presents a new two-dimensional (2-D) phase unwrapping (PhU) algorithm based on a least squares (LS) region growing strategy: the wrapped phase image is partitioned in different regions that are sequentially unwrapped via a LS algorithm. Reliable regions are dealt with at the beginning of the procedure, while critical areas are unwrapped in the final steps, thus avoiding error propagation from critical to reliable areas. A conditioned least squares formulation of the phase unwrapping problem is the core of the proposed procedure: this allows the solution to be tied to "some" known boundary phase values, thus guaranteeing the correct joining of the reconstructed phase in between the different regions and preventing them from being independently unwrapped. The application of the finite element method allows a straightforward implementation of the algorithm in the discrete domain case. Experimental results, carried out on simulated and real interferometric SAR data, show the effectiveness of the proposed algorithm and the improved performances with respect to existing unwrapping procedures.
机译:本文提出了一种基于最小二乘(LS)区域增长策略的新的二维(2-D)相位展开(PhU)算法:包裹的相位图像被划分在不同的区域中,这些区域通过LS算法依次展开。在过程开始时处理可靠区域,而在最后步骤中展开关键区域,从而避免错误从关键区域传播到可靠区域。相位展开问题的条件最小二乘公式表示是所提出程序的核心:这允许将解决方案与“某些”已知边界相位值联系在一起,从而确保不同区域之间重构相位的正确结合并防止它们不会被独立包装。有限元方法的应用允许在离散域情况下直接实现算法。在模拟和真实干涉SAR数据上进行的实验结果表明,该算法的有效性以及相对于现有展开程序的改进性能。

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