Fan-chirp Transform based Thermal Wave Imaging

Non-stationary optical stimulus based infrared non-destructive testing modality has gained much attention from past decades. Various post processing techniques based on signal and image processing have been proposed for better visualization and quantification of subsurface defects for Non-Stationary Thermal Wave Imaging (NSTWD. In present work, a new post processing approach named fan chirp transform is adapted to perfectly match the chirp rate from sample thermal response to facilitate better visualization of defects. The merit of proposed method is compared with the conventional post processing methods like Fast Fourier Transform (FFT) phase, pulse compression (PC) and principle component analysis (PCA). By considering the parameter of merits such as signal to noise ratio of defective pixels and full width at half maxima for defect sizing. It is observed that the adapted Fan-Chirp transform provides better defect detection and better signal to noise ratios.