Pulsed Thermography (PT) data are usually affected by noise and as such most of the research effort in the last few years has been directed towards the development of advanced signal processing methods to improve defect detection. Among the numerous techniques that have been proposed, principal component thermography (PCT)—based on principal component analysis (PCA)—is one of the most effective in terms of defect contrast enhancement and data compression. However, it is well-known that PCA can be significantly affected in the presence of corrupted data (e.g., noise and outliers). Robust PCA (RPCA) has been recently proposed as an alternative statistical method that handles noisy data more properly by decomposing the input data into a low-rank matrix and a sparse matrix. We propose to process PT data by RPCA instead of PCA in order to improve defect detectability. The performance of the resulting approach, Robust Principal Component Thermography (RPCT)—based on RPCA, was evaluated with respect to PCT—based on PCA, using a CFRP sample containing artificially produced defects. We compared results quantitatively based on two metrics, Contrast-to-Noise Ratio (CNR), for defect detection capabilities, and the Jaccard similarity coefficient, for defect segmentation potential. CNR results were on average 40% higher for RPCT than for PCT, and the Jaccard index was slightly higher for RPCT (0.7395) than for PCT (0.7010). In terms of computational time, however, PCT was 11.5 times faster than RPCT. Further investigations are needed to assess RPCT performance on a wider range of materials and to optimize computational time.

In digital holographic and speckle interferometry devoted to solid object displacement measurement, the reflecting properties of the object under study are of importance in designing the observation and laser illumination systems. In practical cases, the objects can show separate zones in which the surface property can simultaneously cause either scattering or specular reflectivity. We present strategies for dealing with both reflectivity types at a time in digital holographic and speckle interferometers. The scattered surface is illuminated with a point source whereas the specular one is illuminated by a diffuser. Both types of surfaces visible across the field-of-view give rise to a specific interferogram with gaps in between, which in turn are interpreted separately related to the sensitivity vector, the latter being defined differently for scattering and specular areas.

We have investigated several full-field contactless techniques, such as thermography and shearography, with several excitation methods for inspecting hybrid composite-metal sandwich structures. The latter are made of a core with epoxy reinforced by carbon and glass fibers and skins of titanium. Several calibrated defects are incorporated at different places in depth and are made of air gaps and inserts.

We apply an inverse-problem-based reconstruction technique to off-axis THz digital holography. Off-axis digital holography configuration at THz regime suffers from non-ideal recording conditions due to the large wavelength. The proposed method takes into account the non-uniformity of the reference wavefront. Compared to the direct Fourier filtering reconstruction, our method reduces the standard deviation of the reconstructed phase.