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Enhanced image processing for infrared non-destructive testing

100%

Lopez F. , Maldague X. , Ibarra-Castanedo C.

2014

tom Vol. 22, No. 4

245-251

This paper presents a review and in-depth analysis of three of the most popular techniques for processing PT images: differential absolute contrast, thermographic signal reconstruction and pulsed phase thermography. The fundamental concepts of the three techniques are reviewed and their application on thermal data obtained from the PT inspection on a carbon fibre reinforced specimen is analysed. Furthermore, a new promissory technique based on multivariate statistical analysis is also introduced and evaluated. The performance of the techniques is evaluated in terms of the signal-to-noise ratio at maximum signal contrast.

Infrared small-target detection under a complex background based on a local gradient contrast method

75%

Yang L. , Xie T. , Liu M. , Zhang M. , Qi S. , Yang J.

International Journal of Applied Mathematics and Computer Science

2023

tom Vol. 33, no. 1

33--43

Small target detection under a complex background has always been a hot and difficult problem in the field of image processing. Due to the factors such as a complex background and a low signal-to-noise ratio, the existing methods cannot robustly detect targets submerged in strong clutter and noise. In this paper, a local gradient contrast method (LGCM) is proposed. Firstly, the optimal scale for each pixel is obtained by calculating a multiscale salient map. Then, a subblockbased local gradient measure is designed; it can suppress strong clutter interference and pixel-sized noise simultaneously. Thirdly, the subblock-based local gradient measure and the salient map are utilized to construct the LGCM. Finally, an adaptive threshold is employed to extract the final detection result. Experimental results on six datasets demonstrate that the proposed method can discard clutters and yield superior results compared with state-of-the-art methods.