## 4 Results and Discussion
However, the PuC-based method demonstrates, as for the sector scan, a better sensitivity for the deepest defects. Figure 9 shows a zoom of the image around defects 3 and 4. Further, also in the case of the TFM, in the PuC images, the defect shapes are closer to the real ones than in the pulse-echo images. Figure 8: TFM image of the CFRP sample obtained from the FMC data captured using the standard and commercial pulse-echo system. The colormap in the images indicates (**a**) the full-wave amplitude, (**b**) the energy, and (**c**) the energy in the dB scale of the echo signal. Figure 2:0 TFM Image of the CFRP sample, obtained using a linear chirp coded excitation signal, and the pulse-compression procedures. The images visualize (**a**) the full-wave amplitude, (**b**) the energy, and (**c**) the energy in the dB scale of the echo signal. The TFM images were obtained by processing the FMC PuC data acquired with different chirp excitation signals and with the second pair of linear transducers. The results are presented in Figures 10-12. The results reported in Figures 7 and 10 are very similar, even though the upper limit of the chirp bandwidth passed from \(\sim\)3 MHz to \(\sim\)4 MHz. This is because the high-frequency components are highly attenuated inside the sample. The results in Figure 11 instead show a slight decrease in the sensitivity with respect to the deepest defects, but even larger than that of the pulse-echo images. Note that the transducers employed to obtain these results in Figure 11 are designed to operate at 4 MHz, but the chirp excitation center frequency was 2.5 MHz, so the transducers did not work in the bandwidth of the highest sensitivity. Figure 2:1 Surface image of the defects no. 3 and no. 4, highlighting the defect detection capability of the used methods. (**a–c**) are the 3D demonstration of the pulse-compression-based TFM images shown in Figure 7, while (**d–f**) are the 3D demonstration of the standard pulse-echo-based TFM images shown in Figure 8, at the location of defects no. 3 and no. 4. Figure 2:2 TFM image of the CFRP sample, but, this time, obtained employing array transducers with a central frequency of 4 MHz while the central frequency of the chirp signal was 2.50 MHz. The image is reconstructed based on the (**a**) the full-wave amplitude, (**b**) the energy, and (**c**) energy in the dB scale of the UT echo signals. Figure 2:3 TFM image of the sample obtained using pulse-compression and chirp excitation signals with a central frequency of 2.25 MHz. The central frequency of the array transducer was 2.25 MHz as well. The image is reconstructed considering (**a**) the full-wave amplitude, (**b**) energy, and (**c**) the energy shown in the dB scale of the echo signals. Moreover, the improvement in the SNR achieved in the PuC-based system can be better understood by looking at the intensity of defects in the TFM images. For this reason, cross-section lines through the position of defects in the TFM images of Figures 7 and 8 are presented in Figure 2:4 Obviously, the higher amplitude of the deepest defects no. 4 and no. 5 in the PuC-based TFM image compared with the one in the standard TFM image is an indicator of the better SNR and sensitivity of the proposed system. Figure 2:5 Surface image of the defects no.3 and no.4. (**a–c**) are the 3D demonstration of the TFM image shown in Figure 10, while (**d–e**) are the 3D demonstration of the TFM image shown in Figure 2:6