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Dual-Frequency Comb Hyperspectral Imaging by Massively Parallelized Infrared Detection and Machine Learning
- Source :
- Optical Sensors and Sensing Congress.
- Publication Year :
- 2020
- Publisher :
- Optica Publishing Group, 2020.
-
Abstract
- Hyperspectral imaging of narrow gas-phase absorption features is demonstrated using massively parallelized dual-frequency comb heterodyne detection. Images are acquired by a 128x128 pixel infrared detector array and reconstructed by a neural network in quasi-real time.
- Subjects :
- Pixel
Artificial neural network
business.industry
Infrared
Computer science
Physics::Optics
Hyperspectral imaging
Computer Science::Computer Vision and Pattern Recognition
Dual frequency
Computer vision
Infrared detector
Artificial intelligence
Heterodyne detection
Absorption (electromagnetic radiation)
business
Astrophysics::Galaxy Astrophysics
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Optical Sensors and Sensing Congress
- Accession number :
- edsair.doi...........544e1a2f006688b1a3905efbdbda4008
- Full Text :
- https://doi.org/10.1364/es.2020.em1c.1