A single-shot phase retrieval method for phase measuring deflectometry based on deep learning

被引：40

作者：

Qiao, Gang ^{[1
]}

Huang, Yiyang ^{[1
]}

Song, Yiping ^{[1
]}

Yue, Huimin ^{[1
]}

Liu, Yong ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Optoelect Sci & Engn, State Key Lab Elect Thin Films & Integrated Devic, Chengdu 610054, Peoples R China

来源：

OPTICS COMMUNICATIONS | 2020年 / 476卷

基金：

中国国家自然科学基金;

关键词：

Phase Measuring Deflectometry (PMD); Fringe analysis; Deep learning; Depthwise separable convolution; FRINGE PATTERN;

D O I：

10.1016/j.optcom.2020.126303

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Phase Measuring Deflectometry (PMD) is an effective metrology technique for specular surfaces, but it is hard to achieve rapid measurement precisely with prevenient fringe analysis methods. Inspired by recent successes of deep learning techniques for fringe analysis, we demonstrate for the first time that deep learning can be used to achieve high-precision three-dimensional (3D) measurement of specular surfaces with a single frame. In this research, it is proposed to use depthwise separable convolution to optimize measured results. Experimental results proved that this proposed method has better performance than the existing fringe analysis method employing deep learning.

引用

页数：8

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