Phase unwrapping by a multi-level grid method for moiré fringes

被引:0
|
作者
Chen, Yunyun [1 ,2 ,3 ,4 ]
He, Chengxing [1 ,3 ,4 ]
Cheng, Weihao [1 ,3 ,4 ]
Xie, Wenzhuo [1 ,3 ,4 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Phys & Optoelect Engn, Nanjing 210044, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Nanjing 210044, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Optoelect Detect Atmosphere Ocean, Nanjing 210044, Peoples R China
[4] Nanjing Univ Informat Sci & Technol, Jiangsu Int Joint Lab Meteorol Photon & Optoelect, Nanjing 210044, Peoples R China
基金
中国国家自然科学基金;
关键词
phase unwrapping; multi-level grid method; moir & eacute; fringe; FLOW-FIELDS; TOMOGRAPHY;
D O I
10.3788/COL202523.021101
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Phase unwrapping is a crucial process in the field of optical measurement, and the effectiveness of unwrapping directly affects the accuracy of final results. This study proposes a multi-level grid method that can efficiently achieve phase unwrapping. First, the phase image of the package to be processed is divided into small grids, and each grid is unwrapped in multiple directions. Then, a level-by-level coarse-graining mesh method is employed to eliminate the new data "faults" generated from the previous level of grid processing. Finally, the true phase results are obtained by iterating to the coarsest grid through the unwrapping process. In order to verify the effectiveness and superiority of the proposed method, a numerical simulation is first applied. Further, three typical flow fields are selected for experiments, and the results are compared with flood-fill and multi-grid methods for accuracy and efficiency. The proposed method obtains true phase information in just 0.5 s; moreover, it offers more flexibility in threshold selection compared to the flood-fill and region-growing methods. In summary, the proposed method can solve the phase unwrapping problems for moir & eacute; fringes, which could provide possibilities for the intelligent development of moir & eacute; deflection tomography.
引用
收藏
页数:7
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