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Regional identification, partition, and integral phase unwrapping method for processing moire interferometry images

机译：莫尔干涉测量图像的区域识别，分区和积分相位展开方法

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摘要

We present a new method of regional identification, partition, and integral (RIPI) phase unwrapping for processing images, especially those with low quality, obtained from moire interferometry experiments. By introducing the principle of preorder traversal of a general tree in data structures and then by applying the idea of a regional integral, the proposed method makes regional partition and phase evaluation much easier and more accurate, and it also overcomes the common faults that can occur when conventional approaches, such as line defects, are used. Examples are given to demonstrate the advantage and applicability of the proposed RIPI method when processing experimental images. It is shown that the proposed method works well for global phase distribution, and, at the same time, local mutational information is preserved and limited to its vicinity without affecting other parts.
机译：我们提出了一种新的区域识别，划分和积分（RIPI）相展开的新方法，用于处理从莫尔干涉测量实验获得的图像，尤其是低质量的图像。通过引入数据结构中一般树的预遍历原理，然后应用区域积分的思想，该方法使区域划分和相位评估变得更加容易和准确，并且还克服了可能发生的常见错误当使用常规方法（例如线缺陷）时。举例说明了所提出的RIPI方法在处理实验图像时的优势和适用性。结果表明，所提出的方法对于全局相位分布很好，同时，局部突变信息被保留并限制在其附近而不影响其他部分。

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