Analysis of Knee Infrared Image Based on Sample Entropy Algorithm

Author(s):  
Shiquan Qiao ◽  
Min Qin ◽  
Hengcao Wang
Author(s):  
Andrew T. Hudak ◽  
Benjamin C. Bright ◽  
Robert L. Kremens ◽  
Matthew B. Dickinson ◽  
Matthew G. Alden

2013 ◽  
Vol 33 (8) ◽  
pp. 2306-2309
Author(s):  
Shaobo DU ◽  
Chong ZHANG ◽  
Chao WANG ◽  
Xiaobin LIANG ◽  
Shibao SUN

2021 ◽  
Vol 113 ◽  
pp. 103012
Author(s):  
Xu Chen ◽  
Lei Liu ◽  
Jingzhi Zhang ◽  
Wenbo Shao

2021 ◽  
Vol 13 (9) ◽  
pp. 1852
Author(s):  
Yiren Wang ◽  
Dong Liu ◽  
Wanyi Xie ◽  
Ming Yang ◽  
Zhenyu Gao ◽  
...  

The formation and evolution of clouds are associated with their thermodynamical and microphysical progress. Previous studies have been conducted to collect images using ground-based cloud observation equipment to provide important cloud characteristics information. However, most of this equipment cannot perform continuous observations during the day and night, and their field of view (FOV) is also limited. To address these issues, this work proposes a day and night clouds detection approach integrated into a self-made thermal-infrared (TIR) all-sky-view camera. The TIR camera consists of a high-resolution thermal microbolometer array and a fish-eye lens with a FOV larger than 160°. In addition, a detection scheme was designed to directly subtract the contamination of the atmospheric TIR emission from the entire infrared image of such a large FOV, which was used for cloud recognition. The performance of this scheme was validated by comparing the cloud fractions retrieved from the infrared channel with those from the visible channel and manual observation. The results indicated that the current instrument could obtain accurate cloud fraction from the observed infrared image, and the TIR all-sky-view camera developed in this work exhibits good feasibility for long-term and continuous cloud observation.


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