Abstract
To compensate for the inability of inexpensive uncooled infrared (IR) sensors to perform high-speed thermography detection with low noise and high sensitivity in the field of non-destructive testing (NDT), a post-processing method for uncooled IR sensors based on compressive sensing is proposed in this paper to perform super-resolution NDT thermography. Super-resolution IR phase images can be generated by first using a sparse representation of the low-resolution (LR) IR images and a sparse dictionary generated from randomly sampled high-resolution (HR) raw training image patches to generate an HR IR image sequence, and, subsequently, implementing IR thermography NDT. To verify the reliability of the proposed method, super-resolution IR images were combined with pulsed phase thermography (PPT) to verify bonded joint structures in carbon fibre-reinforced polymer (CFRP). Compared to other methods, the proposed method reduces the mean square error (MSE) by 11.13% and yields a better visual effect on the PPT phase image reconstructed using three-fold super-resolution. The proposed method not only produces sharp defect edges, but also retains the original texture, which is expected to enable wider application of uncooled IR sensors in NDT applications in the future.
Published Version
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