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A convex hull algorithm based fast large-scale two-dimensional phase unwrapping method

机译:基于凸包算法的快速大规模二维相位解缠方法

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Two-dimensional phase unwrapping (PU) is a critical processing procedure of synthetic aperture radar (SAR) interferometry (InSAR). With the rapid advance of InSAR, the scale of the interferogram is becoming larger and larger. Under the condition of “big-data” PU, there are two new hurdles encountered: i) the dilemma between execution speed and accuracy, ii) the limitation of computing memory. To effectively solve these two problems, a new fast large-scale PU methodology, which is based on the convex hull algorithm and residue clustering characteristics, is discussed in this paper. The theoretical analysis and experiments indicate that this proposed large-scale PU methodology has some desirable potentials for large-scale PU problem: 1) peak memory consumption is very low which can avoid tiling processing; 2) time complexity is approximatively linear; 3) PU solution is as precise as some representative high accuracy PU methods.
机译:二维相位展开(PU)是合成孔径雷达(SAR)干涉测量(InSAR)的关键处理过程。随着InSAR的飞速发展,干涉图的规模越来越大。在“大数据” PU条件下,遇到了两个新的障碍:i)执行速度和准确性之间的困境,ii)计算内存的局限性。为了有效解决这两个问题,本文讨论了一种新的基于凸包算法和残差聚类特性的快速大规模PU方法。理论分析和实验表明,该提出的大规模PU方法具有解决大规模PU问题的潜力:1)峰值内存消耗非常低,可以避免切片处理。 2)时间复杂度近似线性; 3)PU解决方案与某些代表性的高精度PU方法一样精确。

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