Analysis of long-wave Infrared hyperspectral classification performance across changing scene illumination

2019 ◽  
Author(s):  
Nicholas Westing ◽  
Brett Borghetti ◽  
Kevin Gross ◽  
Jacob A. Martin
Keyword(s):  
Classification Performance ◽  
Long Wave ◽  
Hyperspectral Classification ◽  
Scene Illumination ◽  
Long Wave Infrared

RxCADRE 2008: Wildfire Airborne Sensor Program - Lite uncalibrated long wave infrared image mosaics

2016 ◽  
Author(s):  
Andrew T. Hudak ◽  
Benjamin C. Bright ◽  
Robert L. Kremens ◽  
Matthew B. Dickinson ◽  
Matthew G. Alden
Keyword(s):  
Infrared Image ◽  
Long Wave ◽  
Long Wave Infrared

scholarly journals A Bi-Spectral Microbolometer Sensor for Wildfire Measurement

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3690
Author(s):  
Denis Dufour ◽  
Loïc Le Noc ◽  
Bruno Tremblay ◽  
Mathieu N. Tremblay ◽  
Francis Généreux ◽  
...  
Keyword(s):  
Low Resource ◽  
Long Wave ◽  
Radiative Power ◽  
Infrared Radiances ◽  
Moderate Scale ◽  
Long Wave Infrared ◽  
Detector Type ◽  
Experimental Burns ◽  
Fire Radiative Power

This study describes the development of a prototype bi-spectral microbolometer sensor system designed explicitly for radiometric measurement and characterization of wildfire mid- and long-wave infrared radiances. The system is tested experimentally over moderate-scale experimental burns coincident with FLIR reference imagery. Statistical comparison of the fire radiative power (FRP; W) retrievals suggest that this novel system is highly reliable for use in collecting radiometric measurements of biomass burning. As such, this study provides clear experimental evidence that mid-wave infrared microbolometers are capable of collecting FRP measurements. Furthermore, given the low resource nature of this detector type, it presents a suitable option for monitoring wildfire behaviour from low resource platforms such as unmanned aerial vehicles (UAVs) or nanosats.

scholarly journals Data Augmentation and Spectral Structure Features for Limited Samples Hyperspectral Classification

2021 ◽  
Vol 13 (4) ◽  
pp. 547
Author(s):  
Wenning Wang ◽  
Xuebin Liu ◽  
Xuanqin Mou
Keyword(s):  
Classification Accuracy ◽  
Data Augmentation ◽  
Classification Problem ◽  
Classification Performance ◽  
Spectral Structure ◽  
Limited Sample ◽  
Sample Classification ◽  
Training Samples ◽  
Traditional Classification ◽  
Hyperspectral Classification

For both traditional classification and current popular deep learning methods, the limited sample classification problem is very challenging, and the lack of samples is an important factor affecting the classification performance. Our work includes two aspects. First, the unsupervised data augmentation for all hyperspectral samples not only improves the classification accuracy greatly with the newly added training samples, but also further improves the classification accuracy of the classifier by optimizing the augmented test samples. Second, an effective spectral structure extraction method is designed, and the effective spectral structure features have a better classification accuracy than the true spectral features.

Long-wave infrared sub-monolayer quantum dot quantum cascade photodetector

2020 ◽  
pp. 1-1
Author(s):  
Zhijian Shen ◽  
Zhuo Deng ◽  
Xuyi Zhao ◽  
Jian Huang ◽  
Lu Yao ◽  
...  
Keyword(s):  
Quantum Dot ◽  
Quantum Cascade ◽  
Long Wave ◽  
Long Wave Infrared

scholarly journals Two-photon vibrational excitation of air by long-wave infrared laser pulses

2016 ◽  
Vol 94 (2) ◽  
Author(s):  
J. P. Palastro ◽  
J. Peñano ◽  
L. A. Johnson ◽  
B. Hafizi ◽  
J. K. Wahlstrand ◽  
...  
Keyword(s):  
Vibrational Excitation ◽  
Laser Pulses ◽  
Infrared Laser ◽  
Two Photon ◽  
Long Wave ◽  
Long Wave Infrared
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