@inproceedings{a9b6ed2475e4410bb566318671eb297c,
title = "Deep-learning-based deflectometry for simultaneous multi-surface measurement of freeform refractive optics",
abstract = "Due to the highly general surface geometry of freeform optics, the measurement of freeform optical surfaces is still a challenging and rewarding issue. Here, we propose a simultaneous multi-surface measurement method based on deep learning for freeform refractive optics, in which the surfaces are reconstructed based on the transmitted wavefront measured with computer-Aided deflectometry. By adopting the deep learning approaches in geometrical error calibration and wavefront reconstruction, both the efficiency and robustness is significantly improved, and the surface measurement accuracy in the order of nanometers can be achieved. The proposed method provides an effective, robust and accurate way for testing freeform refractive optics with multiple surfaces and a large slope range ",
keywords = "deep learning, deflectometry, system calibration, wavefront reconstruction.",
author = "Zhendong Wu and Daodang Wang and Jinchao Dou and Ming Kong and Lihua Lei and Rongguang Liang",
note = "Funding Information: The activities of this work are supported by Zhejiang Provincial Natural Science Foundation of China (LY21E050016), National Natural Science Foundation of China (NSFC) (51775528). Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Optical Design and Testing XI 2021 ; Conference date: 10-10-2021 Through 12-10-2021",
year = "2021",
doi = "10.1117/12.2601184",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Yongtian Wang and Kidger, {Tina E.} and Osamu Matoba and Rengmao Wu",
booktitle = "Optical Design and Testing XI",
}