Application of blind image quality assessment metrics to pulsed thermography

ABSTRACT

This paper explores the application of Blind Image Quality Assessment (BIQA) metrics to pulsed thermography. Two BIQA were used to subsample a sequence of images acquired using Pulse Thermography (PT). The experiments show that the sequences subsampled using BIQA significantly improve the results when applied to metallic samples but fail to capture informative features on composite materials. On metallic samples, when the PCT is applied, an average improvement of 139% of the Contrast to Noise Ratio (CNR) score is observed, on the sequences subsampled, compared with the entire sequence. Nonetheless, the CNR shows that processing the entire data sequence offers 240% improvement compared with subsampled sequences on composite materials.

KEYWORDS:

• Natural scene statistics
• LWIR
• BIQA
• blind image quality
• active thermography
• material
• defect detection
• pulsed thermography
• GMLOG
• IRNDT

Acknowledgments

This research was supported by the Fonds Quebecois de Recherche - Nature et Technologie (FQRNT).

The authors would like to thank Annette Schwerdtfeger for the time and energy she spent reviewing this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Fonds Québécois de la Recherche sur la Nature et les Technologies [2012-PR- 146354]; National Research Council Canada [496439-2017].

Notes on contributors

J. Fleuret

Julien Fleuret was born in Aix-les-Bains, France, European Union, in 1984. He received an M.Sc in Computer Science at the University of Strasbourg, France, EU in 2012. He is currently a PhD student in Electrical and Computer Engineering at University Laval, Québec, Canada. His centres of interest include the applications of machine learning, data mining and computer vision for pattern recognition, material inspections, and multimodal, and multisensor data fusion.

S. Ebrahimi

Samira Ebrahimi was born in Qaemshahr, Iran, in 1985. She received the B.sc degree in Software engineering and the M.Sc degree in mechatronics engineering in 2008 and 2012, respectively. She is currently a Ph.D. student in electrical and computer engineering at Laval University, Quebec, Canada. Her current research interests are non-destructive testing, machine learning, image processing with application in Infrared thermography.

C. Ibarra-Castanedo

Dr. Clemente Ibarra is a professional researcher in the Computer Vision and Systems Laboratory of Université Laval. He has contributed to several publications in the field of infrared vision. His research interests are in signal processing and image analysis for the nondestructive characterization of materials by active thermography, as well as near and short-wave infrared reflectography/transmittography imaging.

X. Maldague

Pr. Xavier Maldague, P. Eng. PhD is a professor at the Department of Electrical and Computing Engineering of Université Laval, Québec City, Canada (since 1989). He has trained over 50 graduate students (M.Sc., PhD and postdoctoral level) and has more than 500 publications. His research interests are in infrared thermography, Non Destructive Evaluation (NDE) techniques and vision / digital systems for industrial inspection. He holds a Tier 1 Canada Research Chair in Infrared Vision. In 2019 he received an Honoris Causa Doctorate in infrared thermography from the~University of Antwerp (Belgium).