Name: applying hyperspectral reflectance imaging to investigate the palettes and the techniques of painters
Uploaded: 2021-06-18T13:00:00
Description: Watch this Scientific Journal Video about Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters at JoVE.com

This research was funded by Regione Lombardia in the framework of the Project MOBARTECH: una piattaforma mobile tecnologica, interattiva e partecipata per lo studio, la conservazione e la valorizzazione di beni storico-artistici - Call Accordi per la Ricerca e l&#39;Innovazione.
The authors are grateful to the staff at Museo del Novecento for the support during the&#160;in situ&#160;experimental sessions and to the Associazione Pellizza da Volpedo for the access to Studio Museo.

1. Set the spatial resolution of the hypercubes
<ol>
	<li>Perform a preliminary inspection of the painted surface (Figure 1) supported by art experts to identify the main features of the painting.
	<ol>
		<li>Recognize the pictorial techniques employed by the artist to create the painting.</li>
		<li>Identify the different brush strokes of paint on the canvas.</li>
		<li>Estimate, qualitatively, the characteristics of the brush strokes with particular attention to their size.</li>
	</ol>
	...

<ol>
	<li>Picollo, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fiber+Optics+Reflectance+Spectroscopy:+a+non-destructive+technique+for+the+analysis+of+works+of+art.">Fiber Optics Reflectance Spectroscopy: a non-destructive technique for the analysis of works of art.</a> Optical Sensors and Microsystems. , 259-265 (2002).</li><li>Bacci, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-destructive+spectroscopic+investigations+on+paintings+using+optical+fibers.">Non-destructive spectroscopic investigations on paintings using optical fibers.</a> MRS Online Proceedings Library Archive. 267, (1992).</li><li>Liang, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+multispectral+and+hyperspectral+imaging+for+archaeology+and+art+conservation.">Advances in multispectral and hyperspectral imaging for archaeology and art conservation.</a> Applied Physics A. 106, 309-323 (2012).</li><li>Bullock, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reflectance+spectrophotometry+for+measurement+of+colour+change.">Reflectance spectrophotometry for measurement of colour change.</a> National Gallery Technical Bulletin. 2, 49-55 (1978).</li><li>Saunders, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Colour+change+measurement+by+digital+image+processing.">Colour change measurement by digital image processing.</a> National Gallery Technical Bulletin. , 66-77 (1988).</li><li>Appolonia, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combined+use+of+FORS,+XRF+and+Raman+spectroscopy+in+the+study+of+mural+paintings+in+the+Aosta+Valley+(Italy).">Combined use of FORS, XRF and Raman spectroscopy in the study of mural paintings in the Aosta Valley (Italy).</a> Analytical and Bioanalytical Chemistry. 395, 2005-2013 (2009).</li><li>Pouyet, E. 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D., Duran, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+innovative+combination+of+non-invasive+UV-Visible-FORS,+XRD+and+XRF+techniques+to+study+Roman+wall+paintings+from+Seville,+Spain.">An innovative combination of non-invasive UV-Visible-FORS, XRD and XRF techniques to study Roman wall paintings from Seville, Spain.</a> Journal of Cultural Heritage. 22, 1028-1039 (2016).</li><li>Dupuis, G., Elias, M., Simonot, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pigment+identification+by+fiber-optics+diffuse+reflectance+spectroscopy.">Pigment identification by fiber-optics diffuse reflectance spectroscopy.</a> Applied Spectroscopy. 56, 1329-1336 (2002).</li><li>Bacci, M., Picollo, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-destructive+spectroscopic+detection+of+cobalt+(II)+in+paintings+and+glass.">Non-destructive spectroscopic detection of cobalt (II) in paintings and glass.</a> Studies in Conservation. 41, 136-144 (1996).</li><li>Cosentino, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FORS+spectral+database+of+historical+pigments+in+different+binders.">FORS spectral database of historical pigments in different binders.</a> E-Conservation Journal. , 54-65 (2014).</li><li>Leona, M., Winter, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fiber+optics+reflectance+spectroscopy:+a+unique+tool+for+the+investigation+of+Japanese+paintings.">Fiber optics reflectance spectroscopy: a unique tool for the investigation of Japanese paintings.</a> Studies in Conservation. 46, 153-162 (2001).</li><li>Cheilakou, E., Troullinos, M., Koui, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+pigments+on+Byzantine+wall+paintings+from+Crete+(14th+century+AD)+using+non-invasive+Fiber+Optics+Diffuse+Reflectance+Spectroscopy+(FORS).">Identification of pigments on Byzantine wall paintings from Crete (14th century AD) using non-invasive Fiber Optics Diffuse Reflectance Spectroscopy (FORS).</a> Journal of Archaeological Science. 41, 541-555 (2014).</li><li>Kubik, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hyperspectral+imaging:+a+new+technique+for+the+non-invasive+study+of+artworks.">Hyperspectral imaging: a new technique for the non-invasive study of artworks.</a> Physical Techniques in the Study of Art, Archaeology and Cultural. 2, 199-259 (2007).</li><li>Fischer, C., Kakoulli, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multispectral+and+hyperspectral+imaging+technologies+in+conservation:+current+research+and+potential+applications.">Multispectral and hyperspectral imaging technologies in conservation: current research and potential applications.</a> Studies in Conservation. 51, 3-16 (2006).</li><li>Daniel, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hyperspectral+imaging+applied+to+the+analysis+of+Goya+paintings+in+the+Museu+of+Zaragoza+(Spain).">Hyperspectral imaging applied to the analysis of Goya paintings in the Museu of Zaragoza (Spain).</a> Microchemical Journal. 126, 113-120 (2016).</li><li>Baronti, S., Casini, A., Lotti, F., Porcinai, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Principal+component+analysis+of+visible+and+near-infrared+multispectral+images+of+works+of+art.">Principal component analysis of visible and near-infrared multispectral images of works of art.</a> Chemometrics and Intelligent Laboratory Systems. 39, 103-114 (1997).</li><li>Mansfield, J. 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D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrated+X-ray+fluorescence+and+diffuse+visible-to-near-infrared+reflectance+scanner+for+standoff+elemental+and+molecular+spectroscopic+imaging+of+paints+and+works+on+paper.">Integrated X-ray fluorescence and diffuse visible-to-near-infrared reflectance scanner for standoff elemental and molecular spectroscopic imaging of paints and works on paper.</a> Heritage Science. 6, 1-12 (2018).</li><li>Richards, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Remote sensing digital image analysis. 3, (1999).</li><li>Mobaraki, N., Amigo, J. 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Hyperspectral reflectance imaging datasets are large reservoirs of information; therefore, the development of robust and, possibly, automated protocols to analyze the data is a key turn to exploit their potential15,17. The proposed algorithm answers this need in the field of cultural heritage with particular attention to the characterization of the pigments of paintings. Based on SAM20,21, the algorithm s...

Reflectance Spectroscopy (RS) and Fiber Optics Reflectance Spectroscopy (FORS) are based on the detection of the light reflected by surfaces once illuminated by a light source, typically a tungsten-halogen lamp. The output of the acquisition system is constituted by spectra where the reflectance is monitored as a function of the wavelength in a range that depends on the characteristics of the employed experimental setup1,2,3. Introduced during the last four decades4,5, RS and FORS are typically used in combination with X-ray fluorescence and other spectroscopies to describe the materials and the techniques used by artists to realize their masterpieces6,7,8,9. The study of the reflectance spectra is usually performed by comparing the data from the sample with a group of reference spectra selected by the user in personal or public databases. Once the reference spectra that comply with the realization period of the sample and with the&#160;modus operandi&#160;of the artist have been identified, the user recognizes the main features of the reflectance spectra (i.e., transition, absorption, and reflection bands1,2,10,11) and then, with the help of other techniques6,7,8 they distinguish&#160;the pigments that have been used in the paintings. Finally they discusses the slight differences that there exist between the references and the experimental spectra7,9.
In most cases, the experimental datasets are composed of a few spectra, collected from areas chosen by art experts and assumed to be significant for the characterization of the painting6, 12,13. Despite the skills and the experience of the user, a few spectra cannot fully exhaust the characteristics of the whole painted surface. Moreover, the result of the analysis will always be strongly dependent on the expertise of the performer. In this scenario, Hyperspectral Reflectance Imaging (HRI3,14,15) could be a useful resource. Instead of a few isolated spectra, the experimental setups return the reflectance properties of extended portions or even of the whole artefact under investigation16. The two main advantages with respect to the acquisition of the isolated spectra are evident. On one hand, the availability of the spatial distribution of the reflectance properties allows the identification of areas that hide interesting features, even though they may not seem peculiar17. On the other hand, the hypercubes guarantee a number of spectra high enough to enable the statistical analysis of the data. These facts support the comprehension of the distribution of pigments within the painted surface18,19.
With HRI, the comparison of the experimental data with the references could be hard to handle15. A typical detector returns hypercubes of at least 256 x 256 spectra. This would require the user to evaluate more than 65,000 reflectance spectra against each reference, a task almost impossible to be carried out manually in a reasonable time. Therefore, the request for robust and, possibly, automated protocols to manage and analyze HRI datasets is more than justified15,17. The proposed method answers this need by handling the whole analytic procedure with the minimum involvement and the maximum flexibility.
An algorithm comprising a set of home-made codes (Table of Materials) reads, manages, and organizes the files returned by the experimental setup. It allows the fine selection of the portions of the Fields of View (FOVs, one field of view is the area of the painting monitored by a single hypercube) to be studied and performs the analysis of the data based on the Spectral Angle Mapper (SAM) method20,21 and on the manipulation of the original spectra. SAM returns false color gray-scale images called similarity maps. The values of the pixels of these maps correspond to the spectral angles that are the angles between the spectra stored in the hypercubes&#160;and the so-called End Members (EMs, a group of reference spectra that should describe the features of the surface monitored by the hypercubes)22. In the case of RS applied to paintings, the EMs are the reflectance spectra of pigments that should match the palette of the Master. They are chosen based on the available information about the artist, the realization period of the painting, and the expertise of the user. Therefore, the output of the SAM is a set of maps that describes the spatial distributions of these pigments over the painting surface and that supports the user to infer the materials used by the artist and their organization in the artefact. The algorithm offers the possibility of employing all kind of references independently from their origin. The references can be specific spectra selected within the hypercubes, come from databases, be acquired by a different instrument on a different surface (such as samples of pigments or the palette of the artist, for instance), or be obtained employing any kind of reflectance spectroscopy, FORS included.
SAM has been preferred among the available classification methods because it has been demonstrated to be effective for characterizing pigments (refer to the book by Richard23&#160;to have an overview of the main available classification methods).&#160;Instead, the idea of developing a home-made protocol rather than adopting one of the many tools freely available on the net24,25 relies on a practical consideration. Despite the effectiveness and scientific foundation of the existing GUIs and software, a single tool hardly satisfies all the needs of the user. There could be an Input/Output (I/O) issue because a tool does not manage the file containing the raw data. There could be an issue regarding the analysis of the data because another tool does not provide the desired approach. There could be a limitation in the handling of the data because the simultaneous analysis of multiple datasets is not supported. In any case, a perfect tool does not exist. Each method must be adjusted to the data or vice versa. Therefore, the development of a home-made protocol has been preferred.
The presented approach offers neither a complete set of analytical methods (see, for comparison, the tool proposed by Mobaraki and Amigo24) nor an easy-to-manage user-interface (see, for comparison, the software employed by Zhu and co-workers25), but, in exchange, it focuses on a still underrated aspect of hyperspectral data analysis: the opportunity to manipulate the detected spectra. The power of the approach is illustrated by applying it to the painting Quarto Stato by Giuseppe Pellizza da Volpedo (Figure 1), an iconic oil on canvas held in the Museo del Novecento in Milan, Italy. Note that, since the approach requires running home-made codes, the developer arbitrarily chose the names of the codes and both the input and output variables used in the description of the protocol. The names of the variables can be changed by the user but they must be provided as follow: the input and out variables must be written respectively within brackets and eventually separated by comma and within square brackets and eventually separated by a white space.&#160;On the contrary the names of the codes cannot be altered.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>ImageJ/Fiji</td>
			<td>Specim (Oulo, Finlad)</td>
			<td>N/A</td>
			<td>Portable reflectance hyperspectral camera used to acquire the hypercubes</td>
		</tr>
		<tr>
			<td>MATLAB 2019b</td>
			<td>StellarNet Inc (Tampa, Florida, USA)</td>
			<td>N/A</td>
			<td>Portable reflectance spectrometer used to acquire independent reflectance spectra</td>
		</tr>
		<tr>
			<td>Specim IQ Hyperspectral Camera</td>
			<td>National Institutes of Health (Bethesda, Maryland, USA)</td>
			<td>N/A</td>
			<td>&#160;Open source Java image processing program</td>
		</tr>
		<tr>
			<td>StellarNet BLUE-wave Miniature Spectrometer</td>
			<td>&#160;MathWorks (Natick, Massachusset, USA)</td>
			<td>N/A</td>
			<td>Program Language and numerical computing environment</td>
		</tr>
	</tbody>
</table>

applying hyperspectral reflectance imaging to investigate the palettes and the techniques of painters

Reflectance Spectroscopy (RS) and Fiber Optics Reflectance Spectroscopy (FORS) are well-established techniques for the investigation of works of art with particular attention to paintings. Most modern museums put at the disposal of their research groups portable equipment that, together with the intrinsic non-invasiveness of RS and FORS, makes possible the in situ collection of reflectance spectra from the surface of artefacts. The comparison, performed by experts in pigments and painting materials, of the experimental data with databases of reference spectra drives the characterization of the palettes and of the techniques used by the artists. However, this approach requires specific skills and it is time consuming especially if the number of the spectra to be investigated becomes large as is the case of Hyperspectral Reflectance Imaging (HRI) datasets. The HRI experimental setups are multi-dimensional cameras that associate the spectral information, given by the reflectance spectra, with the spatial localization of the spectra over the painted surface. The resulting datasets are 3D-cubes (called hypercubes or data-cubes) where the first two dimensions locate the spectrum over the painting and the third is the spectrum itself (i.e., the reflectance of that point of the painted surface versus the wavelength in the operative range of the detector). The capability of the detector to simultaneously collect a great number of spectra (typically much more than 10,000 for each hypercube) makes the HRI datasets large reservoirs of information and justifies the need for the development of robust and, possibly, automated protocols to analyze the data. After the description of the procedure designed for the data acquisition, we present an analysis method that systematically exploits the potential of the hypercubes. Based on Spectral Angle Mapper (SAM) and on the manipulation of the collected spectra, the algorithm handles and analyzes thousands of spectra while at the same time it supports&#160;the user to unveil the features of the samples under investigation. The power of the approach is illustrated by applying it to Quarto Stato, the iconic masterpiece by Giuseppe Pellizza da Volpedo, held in the Museo del Novecento in Milan (Italy).

The proposed protocol offers a set of interesting features for the management and the analysis of HRI data. The I/O (step 3.1) of the raw data is always the first problem that must be solved before applying any analysis method and it can become a critical issue when dealing with large amounts of data. In the present case, the only task regarding the raw data is to store the experimental results into a dedicated folder and select it by browsing the hard disk when running the reading code (step 3.1.1). Thereafter, the crop...

Watch this Scientific Journal Video about Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters at JoVE.com

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Hyperspectral Reflectance Imaging hypercubes include remarkable information into a large amount of data. Therefore, the request for automated protocols to manage and study the datasets is widely justified. The combination of Spectral Angle Mapper, data manipulation, and a user-adjustable analysis method constitutes a key-turn for exploring the experimental results.

Reflectance Spectroscopy (RS) and Fiber Optics Reflectance Spectroscopy (FORS) are well-established techniques for the investigation of works of art with ...

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