Neural network enabled fringe projection through scattering media

Author:

Yang Shile12ORCID,Shen Yuecheng12ORCID,Luo Jiawei12ORCID,Wang Zhengyang12,Wu Daixuan3ORCID,Liang Jiaming12,Zhang Zhiling2,Qi Dalong2ORCID,Yao Yunhua2ORCID,Deng Lianzhong2,Zhang Bin1ORCID,Sun Zhenrong2,Zhang Shian24ORCID

Affiliation:

1. Sun Yat-sen University

2. East China Normal University

3. South China Normal University

4. Shanxi University

Abstract

The projection of fringes plays an essential role in many applications, such as fringe projection profilometry and structured illumination microscopy. However, these capabilities are significantly constrained in environments affected by optical scattering. Although recent developments in wavefront shaping have effectively generated high-fidelity focal points and relatively simple structured images amidst scattering, the ability to project fringes that cover half of the projection area has not yet been achieved. To address this limitation, this study presents a fringe projector enabled by a neural network, capable of projecting fringes with variable periodicities and orientation angles through scattering media. We tested this projector on two types of scattering media: ground glass diffusers and multimode fibers. For these scattering media, the average Pearson’s correlation coefficients between the projected fringes and their designed configurations are 86.9% and 79.7%, respectively. These results demonstrate the effectiveness of the proposed neural network enabled fringe projector. This advancement is expected to broaden the scope of fringe-based imaging techniques, making it feasible to employ them in conditions previously hindered by scattering effects.

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Fundamental and Applied Basic Research Project of Guangzhou

Science and Technology Commission of Shanghai Municipality

Publisher

Optica Publishing Group

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