Infrared thermography processing using Markov-PCA algorithm

Qingju Tang; Hualu Xing; Li Pan; Hongtao Li; Lei Wang

doi:10.1117/12.2073048

18 December 2014 Infrared thermography processing using Markov-PCA algorithm

Qingju Tang, Hualu Xing, Li Pan, Hongtao Li, Lei Wang

Proceedings Volume 9295, International Symposium on Optoelectronic Technology and Application 2014: Laser Materials Processing; and Micro/Nano Technologies; 92950V (2014) https://doi.org/10.1117/12.2073048
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

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.

Citation Download Citation

Qingju Tang, Hualu Xing, Li Pan, Hongtao Li, and Lei Wang "Infrared thermography processing using Markov-PCA algorithm", Proc. SPIE 9295, International Symposium on Optoelectronic Technology and Application 2014: Laser Materials Processing; and Micro/Nano Technologies, 92950V (18 December 2014); https://doi.org/10.1117/12.2073048

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KEYWORDS

Image processing

Thermography

Infrared imaging

Infrared radiation

Principal component analysis

Coating

Signal to noise ratio

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