Imaging through unknown, random diffusers using diffractive all-optical computing (Conference Presentation)

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

doi:10.1117/12.2632633

4 October 2022 Imaging through unknown, random diffusers using diffractive all-optical computing (Conference Presentation)

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

Author Affiliations +

Proceedings Volume PC12204, Emerging Topics in Artificial Intelligence (ETAI) 2022; PC122040F (2022) https://doi.org/10.1117/12.2632633
Event: SPIE Nanoscience + Engineering, 2022, San Diego, California, United States

Abstract

We report a computer-free method to image through random, new diffusers at the speed of light using passive diffractive optical networks composed of spatially-engineered transmissive layers. These diffractive layers were designed using deep learning in a computer with image pairs containing diffuser distorted optical fields and the corresponding distortion-free images (ground truth). After this one-time training effort, the resulting diffractive layers were fabricated to form a physical network to all-optically reconstruct unknown objects through random, unknown diffusers, without requiring any power except for illumination. This diffractive computational imager might find applications in various fields, e.g., atmospheric sciences, biomedical imaging, defense/security.

Conference Presentation

Citation Download Citation

Yi Luo, Yifan Zhao, Jingxi Li, Ege Çetintaş, Yair Rivenson, Mona Jarrahi, and Aydogan Ozcan "Imaging through unknown, random diffusers using diffractive all-optical computing (Conference Presentation)", Proc. SPIE PC12204, Emerging Topics in Artificial Intelligence (ETAI) 2022, PC122040F (4 October 2022); https://doi.org/10.1117/12.2632633

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