Universal linear processing of spatially incoherent light with diffractive optical processors

Md Sadman Sakib Rahman; Xilin Yang; Jingxi Li; Bijie Bai; Aydogan Ozcan

doi:10.1117/12.3000301

13 March 2024 Universal linear processing of spatially incoherent light with diffractive optical processors

Md Sadman Sakib Rahman, Xilin Yang, Jingxi Li, Bijie Bai, Aydogan Ozcan

Proceedings Volume PC12903, AI and Optical Data Sciences V; PC129030K (2024) https://doi.org/10.1117/12.3000301
Event: SPIE OPTO, 2024, San Francisco, California, United States

Abstract

We report deep learning-based design of diffractive all-optical processors for performing arbitrary linear transformations of optical intensity under spatially incoherent illumination. We show that a diffractive optical processor can approximate an arbitrary linear intensity transformation under spatially incoherent illumination with a negligible error if it has a sufficient number of optimizable phase-only diffractive features distributed over its diffractive surfaces. Our analysis and design framework could open up new avenues in designing incoherent imaging systems with an arbitrary set of spatially-varying point-spread functions (PSFs). Moreover, this framework can also be extended to design task-specific all-optical visual information processors under natural illumination.

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Md Sadman Sakib Rahman, Xilin Yang, Jingxi Li, Bijie Bai, and Aydogan Ozcan "Universal linear processing of spatially incoherent light with diffractive optical processors", Proc. SPIE PC12903, AI and Optical Data Sciences V, PC129030K (13 March 2024); https://doi.org/10.1117/12.3000301

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KEYWORDS

Light sources and illumination

Design and modelling

Information visualization

Optical surfaces

Point spread functions

Multiplexing

Optical coherence

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