Nondestructive testing of GFRP composites with compressive sensing-based terahertz single-pixel imaging

Terahertz (THz) imaging technique has a wide range of applications, from industrial non-destructive testing (NDT) to various biomedical applications. Although the capabilities of terahertz radiation in defect detection are well-proven, the practical limitations have been associated with the long image acquisition time. Hence, to improve the image acquisition speed, the compressive sensing technique has been employed. However, the challenge is identifying the optimal modulation mask for compressive sensing as the image reconstruction metrics hugely depend on the mask. Hence, a systematic investigation of the different modulation masks has been done to reconstruct THz images of glass fibre-reinforced polymer (GFRP) composites using TVAL3 (Total Variation minimization by Augmented Lagrangian and ALternating direction Algorithm). The image reconstruction quality has been studied using mean square error, peak signal-to-noise ratio, and structural similarity index. From the results, it can be noticed with a 0.3 sampling ratio, reliable reconstruction of the THz image is possible, saving 70% of the image acquisition time. Further, the discrete cosine transform (DCT) mask is ideal for high frame rate NDT in low and medium noise scenarios. However, the Bernoulli basis offers high resistance to noise by resulting in the best image reconstruction results at high noise cases, outperforming the DCT.