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INVESTIGATION OF A PAINTING DATING THE FRENCH REVOLUTION USING VISIBLE AND NEAR INFRARED HYPERSPECTRAL IMAGERY S. Le Mouélic1, F. Chauvet1,2, M. Giraud1, E. Le Menn1, Caroline Leynia3, Olivier Barbet4 1 Laboratoire de Planétologie et Géodynamique, CNRS UMR 6112, Université de Nantes, 2 rue de la Houssinière, 44300 Nantes, France. 2 Laboratoire Domaines Océaniques, CNRS UMR 6538, Université de Bretagne Occidentale, France. 3 Art’Cane, Vannes, France. 4 Musée de Bretagne, Rennes, France ABSTRACT We have investigated the potential of visible and infrared hyperspectral imagery to characterize a painting dating from the French revolution. Images at increasingly long wavelengths, probing different depths into the painting, revealed the chronology of the drawings used by the artist. It shows that the two main characters of the drawing have been painted first, followed by the surrounding buildings. The classification of the hyperspectral data set also allowed the automated detection of restored areas, thanks to a different response of the surface varnish. The analysis provided information about the painter technique and allowed the identification and the mapping of the distribution of the main pigments. Figure 1: description of the laboratory hyperspectral facility. 2. CHARACTERISATION OF THE “CLUB BRETON” Index Terms— hyperspectral, paintings, art, infrared PAINTING 1. INTRODUCTION Visible and infrared imaging spectroscopy is a very efficient remote sensing tool to characterize the composition and physical state of a surface. In support for our applications in the domain of planetary exploration and Earth remote sensing, we have set up a laboratory facility to characterize hyperspectral signatures of well controlled mineral, rocks, or man-made artifacts (Fig. 1). This experimental facility is built upon three HySpex cameras (Table 1) from the NEO company, covering the 0.4-2.5 µm wavelength range with a working distance of either 0.3 m or 1 m. spectral Nb line width pixels/line Resolu- camera domain spectral tion (1 (µm) channel m) (width) Figure 2: True color composite of the painting as imaged by the VNIR- 0.4-1.0 160 318 mm 1600 0,198 VNIR HySpex camera. -1 1600 (3,6 nm) mm.p The “Club Breton” painting belongs to the museum of SWIR- 0.9-1.7 147 277 mm 320 0.865 -1 Brittany in Rennes, France. It is supposedly dating few 320i (4,9 nm) mm.p th SWIR- 1.3-2.5 239 277 mm 320 0.865 years after the 20 of June 1792, which corresponds to the 320m (4,8 nm) mm.p -1 event described in the scene, when King Louis XVI was Table 1: characteristics of the three HySpex cameras forced by the revolutionaries to wear the Phrygian cap after they invested the “Palais des Tuileries”. Hyperspectral features appear in this color composite, including again the images of the painting have been acquired with the three restored areas, the original canvas (in particular the upper cameras, using a mosaic of two scans with the painting horizontal line), and the complexity of the sky. mounted on a translation stage. Figure 2 shows the resulting true color image obtained with the VNIR camera. Data have been calibrated in reflectance using a Spectralon as a reference. A series of Kremer pure pigments was also imaged in order to provide a reference database (Fig. 3). Images of the three cameras were studied separately in order to avoid any effect linked to the misregistration of the pixels in the three wavelength domains and to keep the original resolution of the VNIR sensor. Figure 3: VNIR spectra of a subset of the pure pigments from the Kremer collection. 3. ANALYSIS OF THE 400-1000 nm VNIR DOMAIN We have performed a Minimum Noise Fraction analysis of the 160-channels VNIR data cube. The MNF algorithm [1] is used to determine the inherent dimensionality of image data, and then to segregate and equalize the noise in the data. The resulting bands of the MNF transformed data are ranked with the largest amount of variance in the first few bands and decreasing data variance with increasing band number until only noise and no coherent image remains. In our analysis, the first 20 MNF components contain significant spatially coherent information. The first two MNF components are shown in Figures 4a and 4b. The first result which appears readily is the automated detection of Figure 4: up (a) and middle (b): first two MNF components of the restored areas. Examples are pointed out by arrows in the VNIR hyperspectral cube. The second MNF component Figure 4b. Whereas these restored areas were barely reveals all the restored areas (examples are pointed out by detectable at naked eyes, they are easily emphasized by the arrows). Bottom (c) : RGB composite of MNF bands 4,5 and 6, MNF transform thanks to their subtle spectral differences emphasizing the restored areas, the original canvas, and details in the 400-1000 nm domain. Figure 4c shows a color of the drawing such as the complexity of the pigments used for composite of MNF bands number 4, 5 and 6. Several new the sky. In order to go a step further into the analysis, we have 4. ANALYSIS OF THE 0.9-1.7 µm SWIR-i AND THE used the Pixel Purity Index algorithm to detect the most 1.4-2.5 µm SWIR-m DOMAINS extreme spectra in the image, corresponding to the purest pigments. Images of the endmembers distribution have been Three main families of spectral endmembers showed up computed using both the Spectral Angle Mapping (SAM) in the SWIR-I 900-1700 nm range: Pure flat spectra, and the linear unmixing algorithms implemented in the spectra with features at 1210, 1440 and 1520 nm, and ENVI software. The first analysis detected 30 endmembers, spectra with a broad multiple absorption between 1400 and which were grouped in fewer main families of spectra 1600 nm. sharing common properties, and compared to the spectra of the Kremer collection. Figure 6: a. Example of a family of endmembers in the SWIR-i domain, compared with a pure gypsum spectrum from the JPL Figure 5: example of identification of mineral pigments : One of spectral library (spectra are displayed after continuum the spectral endmembers (#12, red line) detected in the image removal). b. Corresponding SAM rule for end-members 8 and using the pixel purity index matches perfectly the Venetian red 11.The gypsum, used in the preparation layer, is spread all over spectrum (black line) of the Kremer pure pigments collection. Its the painting distribution is shown in the classification map at the bottom left. The bottom right image is a true color composite where the The absorption bands in the second end-members contrast has been stretched. family suggest a contribution of Ca-sulfates such as gypsum (Fig. 6a). The spatial distribution of the Figure 5 gives an example of the mineral pigments corresponding end-members (Fig. 6b) does not point to a cartography. One of the spectral endmembers detected by particular feature of the drawing, but rather indicates a the Pixel Purity Index method appears similar to the widespread contribution. This is consistent with the fact spectrum of the Venetian red in the Kremer collection (Fig. that gypsum is known to enter in the composition of the 5a). The Classification with the Spectral Angle Mapping underlying preparation layer of such paintings. technique then allows to identify the areas of the painting We noticed that series of monochromatic images where this particular signature is found (mainly in the extracted from the SWIR-i and SWIR-m domains, which jacket in Figure 5b). illustrate the progressive penetration of radiations through the pictorial coat, allows to document the technique of the This is most probably explained by the fact that the spectral painter (Fig. 7). The disappearance of the buildings below signature is dominated by the substrat and not the very thin the characters hands, seen between 900nm and 1300 nm, pictural layers. suggests that the two central characters were drawn before filling the background. Figure 8: image acquired at 2480 nm, showing the frame of the canvas, the white lead preparatory charge, and the initial outlines of the drawing. 5. CONCLUSION AND PERSPECTIVES The visible and near infrared hyperspectral measurements provided a non-destructive way to analyze the “Club Breton” painting. This method has given new insights into the pictorial matter by revealing the chronology of the sketch used by the painter. The restored areas have been automatically mapped, thanks to their slightly different spectral response. Several details of the technique of the painter have also been emphasized using either the MNF components, or the endmember image fractions. Whereas the qualitative identification of several pigment’s distribution can be obtained, the quantitative evaluation of the pigment concentration is much more difficult due to the intimate mixing of the different components, which results in a highly non-linear behavior Figure 7:Set of monochromatic zoomed images from the SWIR-i of the final spectral signature. Despite this limitation, the and SWIR-m domains, unveiling the chronology of the drawing. non-destructive hyperspectral measurements provide a very Arrows indicate the progressive appearance of buildings in the complementary tool to more conventional techniques in the background. domain of art (e.g. LIBS and Raman Spectroscopy in [2]; and FTIR spectroscopy in [3]) which frequently necessitate The SWIR-m domain proved to be particularly useful as to extract samples from paintings. it provides the deeper penetration depth of the radiation, up to several tens of microns. Fig. 8 displays the 2480 nm 6. REFERENCES image. The coarse canvas frame appears readily through the [1] Boardman, J.W., Kruse, F.A., 1994.