Diffractive optical networks and computational imaging without a computer

Aydogan Ozcan

doi:10.1117/12.2655001

9 March 2023 Diffractive optical networks and computational imaging without a computer

Aydogan Ozcan

Proceedings Volume 12445, Practical Holography XXXVII: Displays, Materials, and Applications; 1244502 (2023) https://doi.org/10.1117/12.2655001
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

We 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 complete their computational task at the speed of light propagation through thin, passive optical layers and have various applications, e.g., all-optical image analysis, feature detection, object classification, computational imaging and seeing through diffusers. They also enable task-specific camera designs and new optical components for, e.g., spatial, spectral and temporal beam shaping, polarization engineering and spatially-controlled wavelength division multiplexing. These deep learning-designed diffractive networks broadly impact (1) all-optical statistical inference engines, (2) computational cameras and microscopes, and (3) inverse design of optical systems that are task-specific.

Conference Presentation

Citation Download Citation

Aydogan Ozcan "Diffractive optical networks and computational imaging without a computer", Proc. SPIE 12445, Practical Holography XXXVII: Displays, Materials, and Applications, 1244502 (9 March 2023); https://doi.org/10.1117/12.2655001

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