Presentation
13 March 2024 Transferring optical information through random unknown diffusers using a diffractive decoder with electronic encoding
Author Affiliations +
Proceedings Volume PC12903, AI and Optical Data Sciences V; PC129030X (2024) https://doi.org/10.1117/12.3000653
Event: SPIE OPTO, 2024, San Francisco, California, United States
Abstract
We report an optical diffractive decoder with an electronic encoder network to facilitate the accurate transmission of optical information of interest through unknown random phase diffusers along the optical path. This hybrid electronic-optical model was trained via supervised learning, and comprises a convolutional neural network-based encoder and jointly-trained passive diffractive layers. After their joint-training using deep learning, our hybrid model can accurately transfer optical information even in the presence of unknown phase diffusers, generalizing to new random diffusers never seen before. We experimentally validated this framework using a 3D-printed diffractive network, axially spanning <70λ, where λ=0.75mm is the illumination wavelength.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuhang Li, Tianyi Gan, Bijie Bai, Çagatay Isil, Mona Jarrahi, and Aydogan Ozcan "Transferring optical information through random unknown diffusers using a diffractive decoder with electronic encoding", Proc. SPIE PC12903, AI and Optical Data Sciences V, PC129030X (13 March 2024); https://doi.org/10.1117/12.3000653
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KEYWORDS
Free space optics

Diffusers

3D modeling

Deep learning

Education and training

Image transmission

Light sources and illumination

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