Applied Physics A

, Volume 121, Issue 3, pp 939–947 | Cite as

Characterizing pigments with hyperspectral imaging variable false-color composites

  • Anita Hayem-GhezEmail author
  • Elisabeth Ravaud
  • Clotilde Boust
  • Gilles Bastian
  • Michel Menu
  • Nancy Brodie-Linder
Invited Paper


Hyperspectral imaging has been used for pigment characterization on paintings for the last 10 years. It is a noninvasive technique, which mixes the power of spectrophotometry and that of imaging technologies. We have access to a visible and near-infrared hyperspectral camera, ranging from 400 to 1000 nm in 80–160 spectral bands. In order to treat the large amount of data that this imaging technique generates, one can use statistical tools such as principal component analysis (PCA). To conduct the characterization of pigments, researchers mostly use PCA, convex geometry algorithms and the comparison of resulting clusters to database spectra with a specific tolerance (like the Spectral Angle Mapper tool on the dedicated software ENVI). Our approach originates from false-color photography and aims at providing a simple tool to identify pigments thanks to imaging spectroscopy. It can be considered as a quick first analysis to see the principal pigments of a painting, before using a more complete multivariate statistical tool. We study pigment spectra, for each kind of hue (blue, green, red and yellow) to identify the wavelength maximizing spectral differences. The case of red pigments is most interesting because our methodology can discriminate the red pigments very well—even red lakes, which are always difficult to identify. As for the yellow and blue categories, it represents a good progress of IRFC photography for pigment discrimination. We apply our methodology to study the pigments on a painting by Eustache Le Sueur, a French painter of the seventeenth century. We compare the results to other noninvasive analysis like X-ray fluorescence and optical microscopy. Finally, we draw conclusions about the advantages and limits of the variable false-color image method using hyperspectral imaging.


Hyperspectral Imaging Cinnabar Hyperspectral Data Blue Pigment Spectral Angle Mapper 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Anita Hayem-Ghez
    • 1
    • 2
    • 3
    Email author
  • Elisabeth Ravaud
    • 1
  • Clotilde Boust
    • 1
    • 4
  • Gilles Bastian
    • 1
  • Michel Menu
    • 1
    • 4
  • Nancy Brodie-Linder
    • 2
    • 5
  1. 1.Centre de Recherche et de Restauration des Musées de FranceParisFrance
  2. 2.Laboratoire de Chimie BiologiqueUniversité de Cergy PontoiseCergy-Pontoise CedexFrance
  3. 3.Fondation des Sciences du PatrimoineUniversité de Cergy PontoiseCergy-Pontoise CedexFrance
  4. 4.UMR8247 CNRS-ENSCP, IRCPParis Sciences et LettresParis Cedex 05France
  5. 5.Laboratoire Léon BrillouinCEA SaclayGif-Sur-YvetteFrance

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