We present a new method of regional identification, partition, and integral (RIPI) phase unwrapping for processing images, especially those with low quality, obtained from moiré 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.
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