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X-ray fluorescence spectroscopy (XRF) plays an important role for elemental analysis in a wide range of scientific fields, especially in cultural heritage. XRF imaging, which uses a raster scan to acquire spectra across artworks, provides the opportunity for spatial analysis of pigment distributions based on their elemental composition. However, conventional XRF-based pigment identification relies on time-consuming elemental mapping by expert interpretations of measured spectra. To reduce the reliance on manual work, recent studies have applied machine learning techniques to cluster similar XRF spectra in data analysis and to identify the most likely pigments. Nevertheless, it is still challenging for automatic pigment identification strategies to directly tackle the complex structure of real paintings, e.g. pigment mixtures and layered pigments. In addition, pixel-wise pigment identification based on XRF imaging remains an obstacle due to the high noise level compared with averaged spectra. Therefore, we developed a deep-learning-based end-to-end pigment identification framework to fully automate the pigment identification process. In particular, it offers high sensitivity to the underlying pigments and to the pigments with a low concentration, therefore enabling satisfying results in mapping the pigments based on single-pixel XRF spectrum. As case studies, we applied our framework to lab-prepared mock-up paintings and two 19th-century paintings: Paul Gauguin's Po\`emes Barbares (1896) that contains layered pigments with an underlying painting, and Paul Cezanne's The Bathers (1899-1904). The pigment identification results demonstrated that our model achieved comparable results to the analysis by elemental mapping, suggesting the generalizability and stability of our model., Comment: 11 pages, 10 figures

Macro x-ray fluorescence (XRF) imaging of cultural heritage objects, while a popular non-invasive technique for providing elemental distribution maps, is a slow acquisition process in acquiring high signal-to-noise ratio XRF volumes. Typically on the order of tenths of a second per pixel, a raster scanning probe counts the number of photons at different energies emitted by the object under x-ray illumination. In an effort to reduce the scan times without sacrificing elemental map and XRF volume quality, we propose using dictionary learning with a Poisson noise model as well as a color image-based prior to restore noisy, rapidly acquired XRF data.

International audience

Part of the collection of the Rubens House in Antwerp is a portrait of young Anthony van Dyck, alternatively attributed to Peter Paul Rubens and his pupil Anthony van Dyck. In order to reconstruct the genesis of the portrait in a manner that improves upon past investigations, a number of high-end technological methods, such as X-radiography, X-ray computer tomography, mammographic tomosynthesis and macroscopic X-ray fluorescence, have been employed to render the overpainted layers visible again. The results of the interdisciplinary examinations of the portrait of the youthful Van Dyck are impressive. The combined results allow the later additions to be peeled away until the original composition can be reached. Several pentimenti are easily discernible and refer to a rather immature hand that makes the authorship of Peter Paul Rubens very unlikely. What emerges is a portrait of an ambitious young man with a luxuriant head of hair and a slightly turned-up collar. The hat and cape were added later. The facial features are more recognisable and the execution of the bold curls points irrefutably in the direction of Anthony van Dyck as the author of his own portrait.

Recent macro-XRF scanning of Rembrandt’s Selfportrait from 1669 in the Mauritshuis – as part of the ReVisRembrandt project – has revealed significantnew information about the pigments and build-up of the painting. The elemental distribution maps make clear that the umber-rich ground plays a very important role in the final appearance of this painting, information that is highly relevant for the study of this self-portrait, as well as many other late Rembrandt paintings. It was also possible and infrared imaging, it is anticipated macro-XRFscanning will become an important diagnostic tool for conservators and art historians alike. to image the presence of organic lakes (by means of the potassium map) and bone black (by means of the calcium and phosphorus maps) in the upper paint layers. In addition to conventional investigative techniques, such as x-radiography and infrared imaging, it is anticipated macro-XRF scanning will become an important diagnostic tool for conservators and art historians alike.

Recent studies in which X-ray beams of macroscopic to (sub) microscopic dimensions were used for non-destructive analysis and characterization of pigments, paint micro samples and/or entire paintings by Vincent van Gogh are concisely reviewed. The overview presented encompasses the use of laboratory and synchrotron radiation-based instrumentation and deals with the use of several variants of X-ray fluorescence (XRF) as a method of elemental analysis and imaging as well as with the combined use of X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS). Microscopic and macroscopic XRF are variants of the method that are well suited to visualize the elemental distribution of key elements, mostly metals, present in paint multi layers, either on the length scale from 1–100 μm inside micro samples taken from paintings or on the 1–100 cm length scale when the (subsurface) distribution of specific pigments in entire paintings is concerned. In the context of the characterization of van Gogh's pigments subject to natural degradation, the use of methods limited to elemental analysis or imaging usually is not sufficient to elucidate the chemical transformations that have taken place. However, at synchrotron facilities, combinations of μ-XRF with related methods such as μ-XAS and μ-XRD have proven themselves to be very suitable for such studies. Their use is often combined with microscopic Fourier transform infra-red (μ-FTIR) spectroscopy since this method delivers complementary information at more or less the same length scale as the X-ray microprobe techniques. Also in the context of macroscopic imaging of works of art, the complementary use of X-ray based and infra-red based imaging appears very promising; some recent developments are discussed.