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首页> 外文期刊>Applied optics >Evaluation of a preconditioned conjugate-gradient algorithm for weighted least-squares unwrapping of digital speckle-pattern interferometry phase maps
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Evaluation of a preconditioned conjugate-gradient algorithm for weighted least-squares unwrapping of digital speckle-pattern interferometry phase maps

机译:数字散斑图干涉相图加权最小二乘解的预处理共轭梯度算法的评估

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摘要

Inasmuch as current fringe analysis techniques used in digital speckle-pattern interferometry (DSPI) yield a phase map module 2 pi, phase unwrapping is the final step of any data evaluation process. The performance of a recently published algorithm used to unwrap DSPI phase maps is investigated. The algorithm is based on a least-squares minimization technique that is solvable by the discrete cosine transform. When phase inconsistencies are present, they are handled by exclusion of invalid pixels from the unwrapping process through the assignment of zero-valued weights. Then the weighted unwrapping problem is solved in an iterative manner by a preconditioned conjugate-gradient method. The evaluation is carried out with computer-simulated DSPI phase maps, an approach that permits the generation of phase fields without inconsistencies, which are then used to calculate phase deviations as a function of the iteration number. Real data are also used to illustrate the performance of the algorithm. (C) 1998 Optical Society of America. [References: 23]
机译:由于数字散斑图案干涉术(DSPI)中使用的当前条纹分析技术会产生相位图模块2 pi,因此相位展开是任何数据评估过程的最后一步。研究了最近发布的用于解开DSPI相图的算法的性能。该算法基于最小二乘最小化技术,该技术可通过离散余弦变换求解。当存在相位不一致时,可通过分配零值权重从展开过程中排除无效像素来处理它们。然后通过预处理的共轭梯度方法以迭代方式解决加权解缠问题。评估是通过计算机模拟的DSPI相图进行的,该方法可以生成没有不一致的相场,然后将其用于计算作为迭代次数函数的相差。实际数据也用于说明算法的性能。 (C)1998年美国眼镜学会。 [参考:23]

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