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Depth-selective chemical imaging of Cultural Heritage Objects (DICHO).

In spite of its ability to successfully characterize the condition and materials of paintings and other works of art in a non-invasive way, Macro X-Ray Fluorescence imaging (MA-XRF) suffers from a drawback that significantly affects its most valued application: revealing hidden features and overpainted compositions. While the penetrative properties of the primary and secondary X-rays can be used beneficially to reveal subsurface information that is crucial for art historical scholars and conservators, the extent to which a particular layer can be visualized selectively depends on the exclusive presence of an element in that layer. By consequence, layers with a similar elemental signature emerge intermixed in the same distribution image while the exact layer sequence remains unclear. As a result, in many cases, (contested) sample extraction proves mandatory in order to assign the detected elements to a specific layer within the paint stratigraphy. In order to augment chemical imaging with an additional depth-dimension, a dual approach is presented: (1) separating surface signals from deeper signals by expanding the MA-XRF detector angle geometry and exploiting the resulting, potential depth information that lies within the absorption effects on emission line ratios, by adding a level of data-processing to the existing protocol; (2) reconstructing the layer buildup and allocation of the detected signals by including an Infrared thermographic camera (IRT). In order to characterize the number of layers present and their sequence, multi-sine heat excitation will be exploited for the spectral range of 1.5-5μm in combination with dedicated post-processing of the hypercube images in the frequency domain. The proposed multimodal MA-XRF+IRT measurement methodology is developed on paint mockups and validated on historical paintings and wood panels, in collaboration with the Royal Museum of Fine Arts Antwerp.
Date:1 Oct 2019 →  30 Sep 2023
Disciplines:Data visualisation and imaging, Heritage and cultural conservation