Next Generation Infrared Imaging Sensors

2011 ◽  
Author(s):  
Andrew Sarangan ◽  
Josh Duran
Keyword(s):  
Infrared Imaging ◽  
Next Generation ◽  
Imaging Sensors

scholarly journals Infrared Imaging Sensors: An Integrated Flexible All‐Nanowire Infrared Sensing System with Record Photosensitivity (Adv. Mater. 16/2020)

2020 ◽  
Vol 32 (16) ◽  
pp. 2070126
Author(s):  
Wenhao Ran ◽  
Lili Wang ◽  
Shufang Zhao ◽  
Depeng Wang ◽  
Ruiyang Yin ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Infrared Sensing ◽  
Sensing System ◽  
Imaging Sensors

scholarly journals Substrate-Based Near-Infrared Imaging Sensors Enable Fluorescence Lifetime Contrast via Built-in Dynamic Fluorescence Quenching Elements

ACS Sensors ◽  
2016 ◽  
Vol 1 (4) ◽  
pp. 427-436 ◽  
Author(s):  
Anand T. N. Kumar ◽  
William L. Rice ◽  
Jessica C. López ◽  
Suresh Gupta ◽  
Craig J. Goergen ◽  
...  
Keyword(s):  
Fluorescence Quenching ◽  
Fluorescence Lifetime ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Near Infrared Imaging ◽  
Imaging Sensors ◽  
Dynamic Fluorescence

scholarly journals Spectral and Radiometric Calibration of the Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG)

2019 ◽  
Vol 11 (18) ◽  
pp. 2129 ◽  
Author(s):  
John W. Chapman ◽  
David R. Thompson ◽  
Mark C. Helmlinger ◽  
Brian D. Bue ◽  
Robert O. Green ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Image Data ◽  
Radiometric Calibration ◽  
Next Generation ◽  
Imaging Spectrometer ◽  
In Situ Data ◽  
Novel Approach ◽  
Infrared Spectrometer ◽  
Calibration Techniques ◽  
Spectrometer Data

We describe advanced spectral and radiometric calibration techniques developed for NASA’s Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). By employing both statistically rigorous analysis and utilizing in situ data to inform calibration procedures and parameter estimation, we can dramatically reduce undesirable artifacts and minimize uncertainties of calibration parameters notoriously difficult to characterize in the laboratory. We describe a novel approach for destriping imaging spectrometer data through minimizing a Markov Random Field model. We then detail statistical methodology for bad pixel correction of the instrument, followed by the laboratory and field protocols involved in the corrections and evaluate their effectiveness on historical data. Finally, we review the geometric processing procedure used in production of the radiometrically calibrated image data.

scholarly journals Methane Mapping with Future Satellite Imaging Spectrometers

2019 ◽  
Vol 11 (24) ◽  
pp. 3054 ◽  
Author(s):  
Alana K. Ayasse ◽  
Philip E. Dennison ◽  
Markus Foote ◽  
Andrew K. Thorpe ◽  
Sarang Joshi ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Infrared Imaging ◽  
Matched Filter ◽  
Signal To Noise Ratio ◽  
Point Sources ◽  
Anthropogenic Sources ◽  
Next Generation ◽  
Imaging Spectrometer ◽  
Satellite Imaging ◽  
Shortwave Infrared

This study evaluates a new generation of satellite imaging spectrometers to measure point source methane emissions from anthropogenic sources. We used the Airborne Visible and Infrared Imaging Spectrometer Next Generation(AVIRIS-NG) images with known methane plumes to create two simulated satellite products. One simulation had a 30 m spatial resolution with ~200 Signal-to-Noise Ratio (SNR) in the Shortwave Infrared (SWIR) and the other had a 60 m spatial resolution with ~400 SNR in the SWIR; both products had a 7.5 nm spectral spacing. We applied a linear matched filter with a sparsity prior and an albedo correction to detect and quantify the methane emission in the original AVIRIS-NG images and in both satellite simulations. We also calculated an emission flux for all images. We found that all methane plumes were detectable in all satellite simulations. The flux calculations for the simulated satellite images correlated well with the calculated flux for the original AVIRIS-NG images. We also found that coarsening spatial resolution had the largest impact on the sensitivity of the results. These results suggest that methane detection and quantification of point sources will be possible with the next generation of satellite imaging spectrometers.

scholarly journals Discriminative Fusion Correlation Learning for Visible and Infrared Tracking

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Xiao Yun ◽  
Yanjing Sun ◽  
Xuanxuan Yang ◽  
Nannan Lu
Keyword(s):  
Infrared Imaging ◽  
Visible Spectrum ◽  
Background Information ◽  
Single Type ◽  
Computationally Efficient ◽  
Model Learning ◽  
Improve Model ◽  
Correlation Learning ◽  
Imaging Sensors ◽  
Infrared Tracking

Discriminative correlation filter- (DCF-) based trackers are computationally efficient and achieve excellent tracking in challenging applications. However, most of them suffer low accuracy and robustness due to the lack of diversity information extracted from a single type of spectral image (visible spectrum). Fusion of visible and infrared imaging sensors, one of the typical multisensor cooperation, provides complementarily useful features and consistently helps recognize the target from the background efficiently in visual tracking. Therefore, this paper proposes a discriminative fusion correlation learning model to improve DCF-based tracking performance by efficiently combining multiple features from visible and infrared images. Fusion learning filters are extracted via late fusion with early estimation, in which the performances of the filters are weighted to improve the flexibility of fusion. Moreover, the proposed discriminative filter selection model considers the surrounding background information in order to increase the discriminability of the template filters so as to improve model learning. Extensive experiments showed that the proposed method achieves superior performances in challenging visible and infrared tracking tasks.

Teledyne Imaging Sensors: infrared imaging technologies for astronomy and civil space

2008 ◽  
Author(s):  
James W. Beletic ◽  
Richard Blank ◽  
David Gulbransen ◽  
Donald Lee ◽  
Markus Loose ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Imaging Technologies ◽  
Imaging Sensors
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