Diffractive optical networks & computational imaging without a computer

Aydogan Ozcan

doi:10.1117/12.2679006

6 October 2023 Diffractive optical networks & computational imaging without a computer

Aydogan Ozcan

Proceedings Volume PC12683, Terahertz Emitters, Receivers, and Applications XIV; PC1268304 (2023) https://doi.org/10.1117/12.2679006
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

I will discuss diffractive optical networks designed by deep learning to all-optically implement various complex functions as the input light diffracts through spatially-engineered surfaces. These diffractive processors designed by deep learning have various applications, e.g., all-optical image analysis, feature detection, object classification, computational imaging and seeing through diffusers, also enabling task-specific camera designs and new optical components for spatial, spectral and temporal beam shaping and spatially-controlled wavelength division multiplexing. These deep learning-designed diffractive systems can broadly impact (1) all-optical statistical inference engines, (2) computational camera and microscope designs and (3) inverse design of optical systems that are task-specific. In this talk, I will give examples of each group, enabling transformative capabilities for various applications of interest in e.g., autonomous systems, defense/security, telecommunications as well as biomedical imaging and sensing.

Conference Presentation

Citation Download Citation

Aydogan Ozcan "Diffractive optical networks & computational imaging without a computer", Proc. SPIE PC12683, Terahertz Emitters, Receivers, and Applications XIV, PC1268304 (6 October 2023); https://doi.org/10.1117/12.2679006

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KEYWORDS

Computational imaging

Optical networks

Optical design

Cameras

Deep learning

Image processing

Imaging systems

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