Deep learning reconstruction enables full-Stokes single compression in polarized hyperspectral imaging

Axin Fan; Tingfa Xu; Geer Teng; Xi Wang; Chang Xu; Yuhan Zhang; Xin Xu; Jianan Li

doi:doi:10.3788/COL202321.051101

Chinese Optics Letters, 2023, 21 (5): 051101, Published Online: May. 10, 2023

Deep learning reconstruction enables full-Stokes single compression in polarized hyperspectral imaging

Axin Fan ^1,2Tingfa Xu ^1,2,*Geer Teng ^1,3Xi Wang ⁴Chang Xu ¹Yuhan Zhang ^1,2Xin Xu ^1,2Jianan Li ^1,**

Author Affiliations

¹ Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of China, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

² Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401151, China

³ Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford OX3 7DQ, UK

⁴ School of Printing & Packaging Engineering, Beijing Institute of Graphic Communication, Beijing 102600, China

Axin Fan, Tingfa Xu, Geer Teng, Xi Wang, Chang Xu, Yuhan Zhang, Xin Xu, Jianan Li. Deep learning reconstruction enables full-Stokes single compression in polarized hyperspectral imaging[J]. Chinese Optics Letters, 2023, 21(5): 051101.

Deep learning reconstruction enables full-Stokes single compression in polarized hyperspectral imaging

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