## 4 Discussion  
Figure 4 shows some typical characteristics of raw thermograms acquired during the application of the employed Legendre pseudo-noise thermal excitation. Figure 4a reports the temperature trends, i.e., the \(y_{\mathcal{TR}}(t)\) curves, corresponding to three different points of the SUT collected by using the setup shown in Figure 3a, that is, the FLIR T660 camera. It can be noted that the heat power was so small that a maximum \(\Delta T\) of 1 \({}^{\circ}\)C was achieved after 62 s of excitation for all the three considered pixels. The temperature gently rose as time elapsed, thus avoiding any possible risk to the SUT. Some defects can be barely detected by analyzing the raw thermograms, but low values of image SNR were reached. In contrast, Figure 5 shows the results obtained after the implementation of the PuC procedure detailed in Figure 1. After PuC, the \"equivalent\" temperature rise is quick and significantly larger than in the raw data case (see Figure 4b). This ensured the higher SNR and defect detection capability, as evident in Figures 5c and 6, where some selected thermograms obtained after PuC at different time instants are reported. The defect \"2\", the splitting \"B\", the wood grain and the subsurface knots are visible. Figure 3: Pulse-compression thermography (PuCT) experimental setups: (**a**) the far-infrared and (**b**) mid-infrared experimental setups. Figure 4: Raw experimental data collected with FLIR T660, i.e. setup (a) in Figure 3: **(a)** raw image of the sample under test (SUT) with three pixels marked on it; **(b)** marked pixels’ raw acquired temperature trends over the whole excitation time: even in the case of pixel 2, in correspondence to a defect, the maximum \(\Delta T\) of 1 \({}^{\circ}\)C was achieved in 62 s of excitation, whereas for a sound pixel it was generally less than 1 \({}^{\circ}\)C; **(c)** selected raw thermograms during the whole acquisition time: even if some defects are visible, the SNR is low. Figure 5: PuCT experimental data collected with FLIR T660, i.e. setup (a) in Figure 3: **(a)** PuCT image of the SUT with three pixels marked on it; **(b)** marked pixels’ equivalent temperature rise after PuC; **(c)** selected thermograms after PuC. To compare the two experimental setups, and thus the use and effectivity of a long-wave (setup (a) and a middle-wave (setup (b) IR camera, Figures 7 and 8 depict the PuCT results obtained by processing the raw data collected with setups (a) and (b), using the same excitation parameters and LED chips system. Figure 6: Selected thermograms obtained after PuCT applied to experimental data collected with FLIR T660, i.e., setup (a). Figure 7: PuCT experimental data collected with Xenics Onca-MWIR-InSb, i.e., setup (b) in Figure 3: (**a**) selected pixels marked; (**b**) marked pixels’ equivalent temperature rise after PuC; (**c**) selected thermograms after PuC. Although very similar results were obtained, the use of the middle-wave IR camera results in a better discrimination between outer and inner structures. The subsurface defects, the knots and the wood grain appear with more contrast by using setup (b), and the inlay pattern disappears almost completely as the time elapses. Conversely, the inlay pattern is always well evident using setup (a). From these preliminary results, we cannot conclude whether this is due to the spectral bandwidth or to the type of sensor used (bolometers for the FLIR T660 vs photodiodes for the Xenics), or that this is related to the type of sensor cooling, but is just a practical observation that corroborates other unpublished tests on historical paintings and wall paintings made with the same setups. Moreover, Figures 5-8 show that the darker parts of the inlay increase in temperature more than the lighter ones (see the picture of the sample in Figures 1 and 3).