Thermal Wave Image Deblurring Based on Depth Residual Network

2021 ◽  
pp. 103847
Author(s):  
Haijun Jiang ◽  
Fei Chen ◽  
Xining Liu ◽  
Jesse Chen ◽  
Kai Zhang ◽  
...  
2021 ◽  
Vol 29 (7) ◽  
pp. 1686-1694
Author(s):  
Qing-jiang CHEN ◽  
◽  
Qian-nan HU ◽  
Jin-yang LI

2011 ◽  
Vol 58-60 ◽  
pp. 1344-1349 ◽  
Author(s):  
Wei Zhang ◽  
Zheng Wei Qiu ◽  
Dong Dong Wang ◽  
Zheng Wei Yang ◽  
Lu Zhu

Defects in the specimen of missile engine shell was detected by thermal wave image technology in this paper. In order to gain intuitionistic and accurate space structure image of the detected object, subtracting background and high-frequency emphasized filtering method were used to enhance the image quality. Then the defect was segmented from the background using particle swarm fuzzy clustering algorithm, while the defect size and depth were identified quantitatively. On this basis, 3D reconstruction of the defect by thermal wave image was recognized by Volume Rendering method. The results show that the precision of the defect quantitative identification is higher, and 3D reconstruction result is well, which help us to observe the location and size of defects intuitionisticly.


2013 ◽  
Vol 313-314 ◽  
pp. 1285-1287
Author(s):  
Yi Ding Zhao ◽  
Shao Peng Hu

A method based on infrared thermal wave to distinguish coal and waste rock is introduced. Infrared thermal wave detection technology, a fast and effective detection method, can detect different characteristics of coal and gangue on the surface or subsurface. Test showed that coal and waste rock can be distinguished effectively by processing their infrared thermal wave image.


1983 ◽  
Vol 44 (C6) ◽  
pp. C6-519-C6-524
Author(s):  
K. R. Grice ◽  
L. J. Inglehart ◽  
L. D. Favro ◽  
P. K. Kuo ◽  
R. L. Thomas

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