Deep-learning-based deflectometry for simultaneous multi-surface measurement of freeform refractive optics

Zhendong Wu; Daodang Wang; Jinchao Dou; Ming Kong; Lihua Lei; Rongguang Liang

doi:10.1117/12.2601184

9 October 2021 Deep-learning-based deflectometry for simultaneous multi-surface measurement of freeform refractive optics

Zhendong Wu, Daodang Wang, Jinchao Dou, Ming Kong, Lihua Lei, Rongguang Liang

Author Affiliations +

Proceedings Volume 11895, Optical Design and Testing XI; 1189504 (2021) https://doi.org/10.1117/12.2601184
Event: SPIE/COS Photonics Asia, 2021, Nantong, JS, China

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

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Citation Download Citation

Zhendong Wu, Daodang Wang, Jinchao Dou, Ming Kong, Lihua Lei, and Rongguang Liang "Deep-learning-based deflectometry for simultaneous multi-surface measurement of freeform refractive optics", Proc. SPIE 11895, Optical Design and Testing XI, 1189504 (9 October 2021); https://doi.org/10.1117/12.2601184

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