## 1 Introduction  
In recent decades, strong efforts have been put into the research of innovative techniques in the field of physics and chemistry applied to cultural heritage (CH) for diagnostic and conservations, based on both the applications of new materials and investigation methods. The main challenge in the CH field is obtaining the greatest quantity of information without provoking any damage to the inspected yet irreplaceable good, i.e., finding an efficient method for diagnostics without modifying their aesthetical appearance. Physical features concerning defects present in such types of objects are obtained using a variety of diagnostic techniques, among which infrared thermography (IRT) is one of the most effective for gathering information about the inner structure of the samples [1]. In particular, optical techniques, such as holographic interferometry (HI), decorrelation, shearography, electronic speckle pattern interferometry (ESPI) and IRT, were used in [2] for artwork diagnostics, while some of these were applied in combination with post-processing algorithms to improve the defect detectability in different CH samples [3; 4; 5; 6; 7; 8]. Moreover, processing methods working in the infrared spectrum have been described and applied by [PERSON] et al. [9], [PERSON] et al. [10; 11], [PERSON] et al. [12] and [PERSON] et al. [13]. In this scenario, a novel strategy based on modulating the heat source via a pseudo-random binary excitation was used in [14] to reduce the risk associated with the use of high-power heating source. The goal of the work was to develop an automatic scheme for detecting faults in the captured images. An efficient scheme based on wavelet subspace decomposition was used, which helped in the identifying of otherwise invisible weaker faults. A new contrast enhancement metric was developed to demonstrate the quantitative efficiency of the algorithm. Subsequently, [PERSON] et al. applied the lock-in technique to shearography [15], [PERSON] et al. [16] described the potentialities of infrared vision to explore sub-surface defects in polychromatic states, and [PERSON] et al. studied CH objects in different sub-spectral infrared bands by using macroscopic reflection mode Fourier transform infrared (MA-rFTIR) [17]. [PERSON] et al. performed active IRT analysis of two stained-glass windows, considering also the possibility to apply the method on in situ characterization [18], while [PERSON] et al. [19] inspected the N. Kessanlis \"Erotica\" photosensitized cement with the aim of developing an integrated methodology for a full-field investigation of complex contemporary artworks. More relevant to the work here introduced, [PERSON] et al. [20] used the pulse-compression thermography (PuCT) technique, using low power light-emitting diode (LED) chips, whose emission was modulated via a pseudo-noise sequence. This approach minimized the heat radiated onto a painted surface while assuring high inspection capabilities. Hyperspectral imaging was employed to detect surface and subsurface features, such as pentimenti and facial contours. The best results obtained by both techniques and post-processing methods (principal and independent component analyses) were fused together. In [21], PuCT and hypercolorimetric multispectral imaging (HMI) were combined for the diagnostic study of historical heritage, providing information on the whole structure of the artworks, identifying surface degradation, different layers, and wood defects and their location within the inner layers of the object. It should be noted that [PERSON] et al. [22] proposed for the first time the use of pseudo-noise excitation and the auto regressive moving average (ARMA) system identification method for the detection of detachments in mural paintings. Other research works concerning the application of non-destructive testing (NDT) in various types of wood pieces assembled together can be found in [23; 24].