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:10.3788/COL202321.051101

Journals >Chinese Optics Letters >Volume 21 >Issue 5 >Page 051101 > Article

Chinese Optics Letters
Vol. 21, Issue 5, 051101 (2023)

Deep learning reconstruction enables full-Stokes single compression in polarized hyperspectral imaging | On the Cover

Axin Fan^1、2, Tingfa Xu^1、2、*, Geer Teng^1、3, Xi Wang⁴, Chang Xu¹, Yuhan Zhang^1、2, Xin Xu^1、2, and Jianan Li^1、**

Author Affiliations

¹Key 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

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

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

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

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DOI: 10.3788/COL202321.051101 Cite this Article Set citation alerts

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 Copy Citation Text

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