All-optical quantitative phase imaging through random diffusers using a diffractive network
Yuhang Li, Yi Luo, Deniz Mengü, Bijie Bai, Aydogan Özcan · 2023
We present a novel approach to perform quantitative phase imaging (QPI) through random phase diffusers using a diffractive neural network consisting of successive diffractive layers optimized using deep learning. This diffractive network is trained to convert the phase information of samples positioned behind random diffusers into intensity variations at the output, enabling all-optical phase recovery and quantitative phase imaging of objects hidden by unknown random diffusers. Unlike traditional digital image reconstruction methods, our all-optical diffractive processor does not require external power beyond the illumination beam and operates at the speed of light propagation.