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Article

Mid-Infrared Compressive Hyperspectral Imaging

1
School of Physics and Optoelectronic Engineering, Xidian University, Xi’an 710071, China
2
National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
3
Department of Computer Science, Universidad Industrial de Santander, Bucaramanga 680002, Colombia
4
Bell Labs, 600 Mountain Avenue, Murray Hill, NJ 07974, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Vladimir Lukin, Karen Egiazarian and Aleksandra Pizurica
Received: 22 January 2021 / Revised: 9 February 2021 / Accepted: 13 February 2021 / Published: 17 February 2021
(This article belongs to the Special Issue Remote Sensing Image Denoising, Restoration and Reconstruction)
Hyperspectral imaging (HSI) has been widely investigated within the context of computational imaging due to the high dimensional challenges for direct imaging. However, existing computational HSI approaches are mostly designed for the visible to near-infrared waveband, whereas less attention has been paid to the mid-infrared spectral range. In this paper, we report a novel mid-infrared compressive HSI system to extend the application domain of mid-infrared digital micromirror device (MIR-DMD). In our system, a modified MIR-DMD is combined with an off-the-shelf infrared spectroradiometer to capture the spatial modulated and compressed measurements at different spectral channels. Following this, a dual-stage image reconstruction method is developed to recover infrared hyperspectral images from these measurements. In addition, a measurement without any coding is used as the side information to aid the reconstruction to enhance the reconstruction quality of the infrared hyperspectral images. A proof-of-concept setup is built to capture the mid-infrared hyperspectral data of 64 pixels × 48 pixels × 100 spectral channels ranging from 3 to 5 μm, with the acquisition time within one minute. To the best of our knowledge, this is the first mid-infrared compressive hyperspectral imaging approach that could offer a less expensive alternative to conventional mid-infrared hyperspectral imaging systems. View Full-Text
Keywords: hyperspectral imaging; mid-infrared; compressed measurement; image reconstruction; side information hyperspectral imaging; mid-infrared; compressed measurement; image reconstruction; side information
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MDPI and ACS Style

Yang, S.; Yan, X.; Qin, H.; Zeng, Q.; Liang, Y.; Arguello, H.; Yuan, X. Mid-Infrared Compressive Hyperspectral Imaging. Remote Sens. 2021, 13, 741. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13040741

AMA Style

Yang S, Yan X, Qin H, Zeng Q, Liang Y, Arguello H, Yuan X. Mid-Infrared Compressive Hyperspectral Imaging. Remote Sensing. 2021; 13(4):741. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13040741

Chicago/Turabian Style

Yang, Shuowen, Xiang Yan, Hanlin Qin, Qingjie Zeng, Yi Liang, Henry Arguello, and Xin Yuan. 2021. "Mid-Infrared Compressive Hyperspectral Imaging" Remote Sensing 13, no. 4: 741. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13040741

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