Spatial-temporal compressive imaging using an unfolding network

Dingaoyu Zhao; Edmund Y. Lam; Jun Ke

doi:10.1364/COSI.2022.CW1B.5

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
Technical Digest Series (Optica Publishing Group, 2022),
paper CW1B.5
•https://doi.org/10.1364/COSI.2022.CW1B.5

Spatial-temporal compressive imaging using an unfolding network

Dingaoyu Zhao, Edmund Y. Lam, and Jun Ke

Computational Optical Sensing and Imaging 2022

Vancouver, British Columbia Canada
11–15 July 2022
ISBN: 978-1-957171-09-8

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Compressive Sensing and Single-Pixel Imaging (CW1B)

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D. Zhao, E. Y. Lam, and J. Ke, "Spatial-temporal compressive imaging using an unfolding network," in Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), Technical Digest Series (Optica Publishing Group, 2022), paper CW1B.5.

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Abstract

We propose an unfolding network GapUNet for spatial-temporal compressive imaging. Simulation and optical experiments demonstrate the network performance using compression ratios of 128: 1 and 16: 1. The mean PSNR of the reconstructed objects is higher than 29dB.

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