Paper
16 October 2019 Improvement of the quality of the interferogram based on the Gaussian process regression
Author Affiliations +
Proceedings Volume 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019); 112051M (2019) https://doi.org/10.1117/12.2542931
Event: Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 2019, Phuket, Thailand
Abstract
Interferometric techniques are very important in the metrology field, while the quality of the interferogram will directly affect the retrieval phase of the tested object. This paper presents a method to improve the quality of the interferogram including restoration of noise aliasing and moiré distortion by using the Gaussian Process Regression (GPR). Through choosing a suitable covariance function to describe the relationship between points and points in the fringe pattern, we build a Gaussian process regression model of interferogram, denoise the interferogram and improve the resolution at the same time. The treated interferogram can predict and compensate the part of the fringe distortion and enlarge the depth range of the interferometric measurement. Besides, with the resolution elevated of the hologram, a wider spectrum range can be obtained. In order to verify the possibility of this method, several simulations have been done, which showed a good performance in the enhancement of the quality of interferogram.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dingfu Chen, Yingjie Yu, and Jiaqi Shi "Improvement of the quality of the interferogram based on the Gaussian process regression", Proc. SPIE 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 112051M (16 October 2019); https://doi.org/10.1117/12.2542931
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KEYWORDS
General packet radio service

Fringe analysis

Data modeling

Process modeling

Interferometry

Computer generated holography

Distortion

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