Non-destructive testing of CFRP using pulsed thermographic data enhanced by wavelet transform-based image denoising

Pulsed thermography (PT) is a widely used non-destructive testing (NDT) technique for defect detection in carbon fiber reinforced polymers (CFRP) structures. Thermographic signal reconstruction (TSR) is often employed to process thermographic data due to its excellent performance in enhancing the contrast between defects and background. However, TSR does not reduce the noise of thermographic data effectively. To solve this problem, this thesis proposes an image denoising method based on wavelet transform. The experiment results show that dealt with wavelet transform the characteristics of the defective regions are more clearly compared with previous images. And the signal-to-noise ratio (SNR) values are improved obviously at the same time.