Deep learning for snapshot compressive imaging

Xin Yuan

doi:10.1364/ISA.2021.IW4A.1

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2021),
paper IW4A.1
•https://doi.org/10.1364/ISA.2021.IW4A.1

Deep learning for snapshot compressive imaging

Xin Yuan

Imaging Systems and Applications 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-89-7

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Machine Learning and Imaging I (IW4A)

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X. Yuan, "Deep learning for snapshot compressive imaging," in OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), H. Hua, B. Javidi, M. Martinez-Corral, O. Matoba, A. Stern, S. Thibault, T. Alieva, J. Ke, F. Willomitzer, F. Okten, P. Silveira, P. Banerjee, E. Stoykova, D. Chu, J. Park, F. Imai, C. Joo, M. Digman, D. Gardner, S. Gladysz, D. LeMaster, S. Basu, and O. Korotkova, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper IW4A.1.

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Abstract

We consider deep learning methods for snapshot compressive imaging (SCI), where a single 2D detector is used to capture the high-dimensional data-cube. This work reviews the recent advances of deep learning based inversion algorithms for SCI.

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