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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing. >Large-Scale L0 -Norm and L1 -Norm 2-D Phase Unwrapping
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Large-Scale L0 -Norm and L1 -Norm 2-D Phase Unwrapping

机译:大型L0-范数和L1-范数2-D相展开

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摘要

Two-dimensional phase unwrapping (PU) is a crucial processing step of synthetic aperture radar interferometry (InSAR). With the rapid advance of InSAR technology, the scale of interferograms is becoming increasingly larger. When the size of the input interferogram exceeds computer hardware capabilities, PU becomes more problematic in terms of computational and memory requirements. In the case of “big-data” PU, the input interferogram needs to be first tiled into a number of subinterferograms, unwrapped separately, and then spliced together. Hence, whether the PU result of each subinterferogram is consistent with that of the whole interferogram is critical to the large-scale PU process. To effectively solve this problem, the L1 -norm envelope-sparsity theorem, which gives a sufficient condition to exactly guarantee the consistency between local and global L1 -norm PU solutions, is put forward and proved. Furthermore, the L0 -norm envelope-sparsity theorem, which gives a sufficient condition to exactly guarantee the consistency between local and global L0 -norm PU solutions, is also proposed and proved. Afterward, based on these two theorems, two tiling strategies are put forward for the large-scale L0 -norm and L1 -norm PU methods. In addition, this paper presents the concepts of the tiling accuracy and the tiling resolution, which are the criteria used to evaluate the effectiveness of a tiling strategy, and we use them to quantitatively analyze the aforementioned tiling strategies. Both theoretical analysis and experimental results show that the proposed tiling strategies are effective for the large-scale L0 -norm and L1 -norm PU problems.
机译:二维相位展开(PU)是合成孔径雷达干涉仪(InSAR)的关键处理步骤。随着InSAR技术的飞速发展,干涉图的规模越来越大。当输入干涉图的大小超过计算机硬件功能时,PU在计算和内存需求方面会变得更加棘手。在“大数据” PU的情况下,需要先将输入干涉图平铺为多个子干涉图,分别展开,然后再拼接在一起。因此,每个子干涉图的PU结果是否与整个干涉图的一致,这对于大规模的PU处理至关重要。为了有效地解决这个问题,提出并证明了L1-范数包络稀疏性定理,该定理为充分保证局部和全局L1-范数PU解之间的一致性提供了充分的条件。此外,还提出并证明了L0范数包络稀疏定理,该定理为充分保证局部和全局L0范数PU解之间的一致性提供了充分的条件。然后,基于这两个定理,针对大规模的L0范数和L1范数PU方法提出了两种平铺策略。另外,本文提出了切片精度和切片分辨率的概念,这是用于评估切片策略有效性的标准,并且我们将它们用于对上述切片策略进行定量分析。理论分析和实验结果均表明,所提出的平铺策略对于大规模的L0-范数和L1-范数PU问题是有效的。

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