The Research of Non-Uniformity Correction of Infrared Image in Thermal Wave Testing Based on Homomorphism Technology

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Abstract:

The infrared thermal wave technology is a new nondestructive testing (NDT) method with a kind of advantage, including non-contact, intuitionistic, fast et al. But the infrared images always have defects that the low-contrast and high-noise due to uneven brightness and calefaction in the testing process, which enhance the difficulty of following quantitative distinguishment of defects. Therefore, the improved homomorphic filtering is given in this article. The detailed processes of the method and testing results are given. The results of the experiments show that the method has higher peak signal to noise ratio (PSNR), can improve image quality, which establish basis for future research of image segmentation.

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2376-2380

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June 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] WANG Xun, JIN Wanping, ZHANG Cunlin and SHEN Jingling. Actuality & Evolvement of Infrared Thermal Wave Nondestructive Imaging Technology [J], Journal of NDT, 2004, 26(10): 497~501.

Google Scholar

[2] CHEN Rui, TAN Xinquan. Study on Non-uniformity Correction of Infrared Image [J]. Optoelectronic Technology, 2003, 23(2): 135~138.

Google Scholar

[3] Hormans R, HePfer K C, Zurasky M. Uniformity compensation for high quantum efficiency focal arrays [J]. Proc. SPIE. 1996. 2744: 154~164.

DOI: 10.1117/12.243460

Google Scholar

[4] ZHENG Ruihong. The scene-based methods of nonuniformity correction [D]. Nanjing University of Science & Technology. (2003).

Google Scholar

[5] ZHU Xi-chang, LIU Feng, HU Dong. Digital image processing and image communication [M], Beijing post and Telecommunication press. 2005. 5.

Google Scholar

[6] LUO Jun-hui, FENG Ping,Application of Matlab 7. 0 in image processing [M], China Machine Press. 2007. 7.

Google Scholar

[7] Damera-Venkata N, et al. Image quality assessment based on a degradation model [J]. IEEE Trans. on Image Process, 2004, 9(4): 636-650.

DOI: 10.1109/83.841940

Google Scholar