Search Results for author: Che-Yung Shen

Found 6 papers, 0 papers with code

Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processor

no code implementations16 Mar 2024 Che-Yung Shen, Jingxi Li, Tianyi Gan, Yuhang Li, Langxing Bai, Mona Jarrahi, Aydogan Ozcan

These wavelength-multiplexed patterns are projected onto a single field-of-view (FOV) at the output plane of the diffractive processor, enabling the capture of quantitative phase distributions of input objects located at different axial planes using an intensity-only image sensor.

Multiplexed all-optical permutation operations using a reconfigurable diffractive optical network

no code implementations4 Feb 2024 Guangdong Ma, Xilin Yang, Bijie Bai, Jingxi Li, Yuhang Li, Tianyi Gan, Che-Yung Shen, Yijie Zhang, Yuzhu Li, Mona Jarrahi, Aydogan Ozcan

We demonstrated the feasibility of this reconfigurable multiplexed diffractive design by approximating 256 randomly selected permutation matrices using K=4 rotatable diffractive layers.

All-optical complex field imaging using diffractive processors

no code implementations30 Jan 2024 Jingxi Li, Yuhang Li, Tianyi Gan, Che-Yung Shen, Mona Jarrahi, Aydogan Ozcan

Here, we present a complex field imager design that enables snapshot imaging of both the amplitude and quantitative phase information of input fields using an intensity-based sensor array without any digital processing.

Image Reconstruction

All-Optical Phase Conjugation Using Diffractive Wavefront Processing

no code implementations8 Nov 2023 Che-Yung Shen, Jingxi Li, Tianyi Gan, Mona Jarrahi, Aydogan Ozcan

Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with various applications ranging from imaging to beam focusing.

Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network

no code implementations5 Aug 2023 Che-Yung Shen, Jingxi Li, Deniz Mengu, Aydogan Ozcan

Here, we present the design of a diffractive processor that can all-optically perform multispectral quantitative phase imaging of transparent phase-only objects in a snapshot.

Unidirectional Imaging using Deep Learning-Designed Materials

no code implementations5 Dec 2022 Jingxi Li, Tianyi Gan, Yifan Zhao, Bijie Bai, Che-Yung Shen, Songyu Sun, Mona Jarrahi, Aydogan Ozcan

A unidirectional imager would only permit image formation along one direction, from an input field-of-view (FOV) A to an output FOV B, and in the reverse path, the image formation would be blocked.

Blocking

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