Seeing through unknown, random diffusers using all-optical diffractive networks

Yi Luo; Yifan Zhao; Jingxi Li; Ege Çetintas; Yair Rivenson; Mona Jarrahi; Aydogan Ozcan

doi:10.1117/12.2609811

9 March 2022 Seeing through unknown, random diffusers using all-optical diffractive networks

Yi Luo, Yifan Zhao, Jingxi Li, Ege Çetintas, Yair Rivenson, Mona Jarrahi, Aydogan Ozcan

Proceedings Volume PC12019, AI and Optical Data Sciences III; PC120190N (2022) https://doi.org/10.1117/12.2609811
Event: SPIE OPTO, 2022, San Francisco, California, United States

Abstract

We report an all-optical computational imager to restore diffuser-distorted images at the speed of light, without a computer. For seeing through random/unknown diffusers, we trained diffractive networks consisting of successive transmissive layers. After its training, the resulting diffractive layers are fabricated, forming a passive optical network, placed behind random, new diffusers to perform all-optical reconstruction of unknown images entirely covered by unknown diffusers. All-optical diffractive reconstructions are completed at the speed of light propagation from the input to the output, do not require power except for illumination, and might find applications in e.g., atmospheric sciences, biomedical imaging, defense/security, among others.

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Citation Download Citation

Yi Luo, Yifan Zhao, Jingxi Li, Ege Çetintas, Yair Rivenson, Mona Jarrahi, and Aydogan Ozcan "Seeing through unknown, random diffusers using all-optical diffractive networks", Proc. SPIE PC12019, AI and Optical Data Sciences III, PC120190N (9 March 2022); https://doi.org/10.1117/12.2609811

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