This paper presents the application of polynomial fitting techniques to eliminate the non-uniform heating effect and enhance
the infrared (IR) image thermal contrast for infrared thermography (IRT) inspection. The raw thermal images acquired in IRT
nondestructive evaluation (NDE) are usually corrupted by the non-uniform heating effect to some extent and suffer image
degradation due to the low signal-to-noise ratio (SNR) and low temperature contrast. Especially for carbon composites,
anisotropic material properties and inhomogeneous densities make the IRT NDE job challenging. In order to obtain clear IR
images and aid NDE inspectors in making quick, accurate, and reliable decisions, polynomial curve fitting and surface fitting
techniques based on the least squares method are utilized to reconstruct the infrared thermal noise-free signal and estimate
the non-uniform heating pattern respectively. Then, the non-uniform heating effect will be eliminated by subtracting the
estimated pattern from the corrupted IR image. The results obtained demonstrate that this applied method not only removes
the non-uniform heating effect, but also greatly improves the image quality in IRT inspection. We believe this technique can
make the defect evaluation process much easier and more accurate, and it has particular value in IRT defect diagnosis.
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