Simulations of AIRS spectral response function measurement with an FTS

1997 ◽  
Author(s):  
Paul F. W. van Delst ◽  
Henry E. Revercomb ◽  
Robert O. Knuteson ◽  
Hartmut H. Aumann ◽  
Kenneth Overoye
Keyword(s):  
Response Function ◽  
Spectral Response ◽  
Function Measurement

scholarly journals Response function measurement of layered type CVD single crystal diamond radiation detectors for 14 MeV neutrons

2004 ◽  
Vol 75 (10) ◽  
pp. 3581-3584 ◽  
Author(s):  
J. H. Kaneko ◽  
T. Teraji ◽  
Y. Hirai ◽  
M. Shiraishi ◽  
S. Kawamura ◽  
...  
Keyword(s):  
Single Crystal ◽  
Response Function ◽  
Radiation Detectors ◽  
Function Measurement ◽  
Single Crystal Diamond

scholarly journals Blind Fusion of Hyperspectral Multispectral Images Based on Matrix Factorization

2021 ◽  
Vol 13 (21) ◽  
pp. 4219
Author(s):  
Jian Long ◽  
Yuanxi Peng
Keyword(s):  
Response Function ◽  
Spatial Resolution ◽  
Point Spread Function ◽  
Spectral Response ◽  
Estimation Method ◽  
Hyperspectral Images ◽  
Fusion Method ◽  
Multispectral Images ◽  
Point Spread ◽  
Spread Function

The fusion of low spatial resolution hyperspectral images and high spatial resolution multispectral images in the same scenario is important for the super-resolution of hyperspectral images. The spectral response function (SRF) and the point spread function (PSF) are two crucial prior pieces of information in fusion, and most of the current algorithms need to provide these two preliminary pieces of information in advance, even for semi-blind fusion algorithms at least the SRF. This causes limitations in the application of fusion algorithms. This paper aims to solve the dependence of the fusion method on the point spread function and proposes a method to estimate the spectral response function from the images involved in the fusion to achieve blind fusion. We conducted experiments on simulated datasets Pavia University, CAVE, and the remote sensing images acquired by two spectral cameras, Sentinel 2 and Hyperion. The experimental results show that our proposed SRF estimation method can improve the PSNR value by 5 dB on average compared with other state-of-the-art SRF estimation results. The proposed blind fusion method can improve the PSNR value of fusion results by 3–15 dB compared with other blind fusion methods.

Detector level ABI spectral response function: FM4 analysis and comparison for different ABI modules

2016 ◽  
Author(s):  
Boryana Efremova ◽  
Aaron J. Pearlman ◽  
Frank Padula ◽  
Xiangqian Wu
Keyword(s):  
Response Function ◽  
Spectral Response
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