Deep learning assisted optical wavefront shaping in disordered medium

• Main Authors: Luo, Yunqi, Li, Huanhao, Zhang, Ruochong, Lai, Puxiang, Zheng, Yuanjin
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Wavefront Shaping; Deep Learning
• Online Access: https://hdl.handle.net/10356/142286
• Institution: Nanyang Technological University

Wavefront shaping (WFS) has been put forward several years ago to break the limitation caused by optical scattering in inhomogeneous medium, and realize optical focusing in disordered medium like biological tissues. However, usually, with traditional methods, WFS is time consuming and not cost efficient since it requires long time to obtain the information of the scattering medium. Here we propose the deep learning assisted wavefront shaping, which uses deep neural networks to predict the desired input optical modes that are needed to realize focusing after light passes through a scattering medium. Simulation results show that the pre-trained neural network is able to map output optical modes to input modes. Compared with previous methods which use iterative optimization, our method realizes a focused speckle pattern with the help of deep learning, which will definitely reduce complexity and time spent in optimization. Experiments will be conducted soon.