## 3 Results and Discussion
Of course, the number of needed computations increases, but it should be kept in mind that all the computations related to the fictitious \"zero frame\" pixels are left out. In addition to enhanced resolution, a more distinct continuity of change in pixel intensity is apparent, which corresponds to the defects (especially those with the largest diameter). This ensured better insight into the thermal process dynamics and facilitated assessment of relative depth ratios. Figure 4: Deviation of values on curves B, C, D and E shown in Figure 3 from those of curve Sa: (a) B-Sa, (b) C-Sa, (c) D-Sa and (d) E-Sa. Figure 5: Defect phase contrast obtained by processing every 3 rd, 6 th, 9 th and 12 th frame (top down): Procedure A left, Procedure B right. Defects can be detected at a certain (specific) depth based on the phase contrast in the frequency domain, but only after the sampling frequency drops to below the blind frequency [18]. The limiting frequency is higher if the defect is shallower. It is apparent that the defects along vertical E became visible only after the sampling frequency was low enough, or when the value of step \(k\) in the FOR NEXT loop became greater than 3 in data processing. It is apparent that the time lag of the peak of the corresponding curve, in Figure 4, is the longest in the case of the defects along vertical E. Namely, it corresponds to the defect that is most distant from the heated surface. Obviously, there is a correlation with the results shown in Figs. 4 and 5. As the distance of the defects (of the same radii) increases, viewed relative to the heated surface, so does the time lag. This is consistent with the fact that a longer sampling period, or a lower blind frequency, is required for them to be visible. The relative phase contrast ratios, shown as differences in gray scale in Figures 5 and 6, were fully correlated with the detected defect depth. The shallowest defects were the lightest, as the phase contrast, determined by the temperature change after test sample irradiation, was the highest there [18]. A quantitative description of this is given in Figure 7 using curves that represent the change in the mathematical expectation of the gray scale in Figures 5 and 6, within areas whose boundaries coincide with areas B, C, D and E in Figure 2.  
In order to better illustrate the thermal process within the largest-diameter defects, Figures 8-10 show the change in intensity of the pixels positioned in the interval from 101 to 140, within the broken  
Figure 6: Defect phase contrast obtained by processing every 15 th, 18 th, 21 st and 24 th frame (top down): Procedure A left, Procedure B right. Figure 7: Intensity equivalent of phase contrast versus \(f_{\mathrm{s}}/k\) ratio for \(\emptyset=15\) mm defects: circles, squares, pentagrams and triangles along vertical B, C, D and E, respectively. lines shown in Figure 11, whose vertical coordinates correspond to the values 62, 67, 73, 80, 83 and 87. The change in pixel intensity during the first 200 frames is shown in color, where blue is the initial, minimum value and dark red is the maximum intensity immediately after test sample irradiation. Figure 8: Pixel intensity variation along lines 62 (top) and 67 (bottom). Figure 3:0 Pixel intensity variation along lines 82 (top) and 87 (bottom). Figure 3:1 Pixel intensity variation along lines 73 (top) and 80 (bottom). The temperature variation over time is apparent, but so are the effects of lateral diffusion (as in the case of line 82 in Figure 10, top). In the specific case, the central part that corresponded to the 120 th pixel exhibited a lower intensity than the pixels to the immediate left and right. This clearly shows that after initial heating, upon irradiation of the test sample, the heat started to spread from the center to the periphery of the defect.