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Multispectral IR Reflectography for Painting Analysis

  • Raffaella Fontana
  • Marco Barucci
  • Alice Dal Fovo
  • Enrico Pampaloni
  • Marco Raffaelli
  • Jana Striova
Chapter

Abstract

InfraRed Reflectography (IRR) is traditionally used in the non-destructive diagnostics of ancient paintings to reveal features underlying the pictorial layer thanks to transparency characteristics to IR radiation of the materials composing the paints. Generally performed in wide-band modality, consisting in the acquisition of the radiation backscattered by a painting in a spectral range that depends on the detector used, it has recently been improved with the multispectral modality. Multi-spectral IR reflectography, based on reflectance measurement in narrow spectral bands, is presented herein. Main technologies, using either filters or dispersive systems, and the innovative scanner for multispectral IR reflectography are described. A few examples of application are shown, to highlight both the potential of multispectral analysis and its advantages over wide-band reflectography. The output is a stack of monochromatic images, one for each selected wavelength, which can be analysed separately as well as jointly. The multispectral option allows the choice of the most effective IR bands improving the ability to detect hidden features; interband comparison aids in localizing areas of different pictorial materials with particular IR reflectance. Besides the analysis of single monochromatic images, the joint processing of multispectral planes, such as subtraction and ratio methods, false colour representation and statistical tools, aids in enhancing details from hidden layers and providing information synthetized in a single image. Maintaining a visual approach in the data analysis allows this tool to be used by restorers and conservators, the actual end-users.

Notes

Acknowledgements

The authors would like to thank Dr. Cecilia Frosinini and Roberto Bellucci for the fruitful discussions necessary for a proper interpretation of the results. We would also thank Marta Florez Igual for preparing the cobalt blue sample presented herein.

This research has been co-financed by H2020 IPERION CH project (contract number: 654028).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Raffaella Fontana
    • 1
  • Marco Barucci
    • 1
  • Alice Dal Fovo
    • 1
  • Enrico Pampaloni
    • 1
  • Marco Raffaelli
    • 1
  • Jana Striova
    • 1
  1. 1.CNR-INO, National Institute of Optics - National Research CouncilHeritage Science GroupFlorenceItaly

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