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Proceedings Paper

Infrared thermography processing using Markov-PCA algorithm
Author(s): Qingju Tang; Hualu Xing; Li Pan; Hongtao Li; Lei Wang
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Paper Abstract

The pulsed infrared thermal image sequence characteristics of the coating structure was analyzed, and the temperature change process of any pixel including status and time parameters was considered as discrete Markov process. A combination of Markov and principal component analysis (PCA) algorithm were proposed to process the pulsed infrared image sequence. First, using the Markov method to achieve the image sequence reconstruction, then using PCA method to achieve the original complex data dimensionality reduction to remove the noise and redundancy, and extract the main components reflecting the main features of the data. Results show that the processed images have higher SNR. Results show that the processed images have much higher SNR than that of the original thermal image with the best contrast.

Paper Details

Date Published: 18 December 2014
PDF: 4 pages
Proc. SPIE 9295, International Symposium on Optoelectronic Technology and Application 2014: Laser Materials Processing; and Micro/Nano Technologies, 92950V (18 December 2014); doi: 10.1117/12.2073048
Show Author Affiliations
Qingju Tang, Heilongjiang Univ. of Science and Technology (China)
Hualu Xing, Northwestern Polytechnical Univ. (China)
Li Pan, Heilongjiang Univ. of Science and Technology (China)
Hongtao Li, Heilongjiang Univ. of Science and Technology (China)
Lei Wang, Heilongjiang Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 9295:
International Symposium on Optoelectronic Technology and Application 2014: Laser Materials Processing; and Micro/Nano Technologies
Guofan Jin; Songlin Zhuang; Jennifer Liu, Editor(s)

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