Sensors (Oct 2019)

Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography

  • Stefano Laureti,
  • Hamed Malekmohammadi,
  • Muhammad Khalid Rizwan,
  • Pietro Burrascano,
  • Stefano Sfarra,
  • Miranda Mostacci,
  • Marco Ricci

DOI
https://doi.org/10.3390/s19194335
Journal volume & issue
Vol. 19, no. 19
p. 4335

Abstract

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The use of different spectral bands in the inspection of artworks is highly recommended to identify the maximum number of defects/anomalies (i.e., the targets), whose presence ought to be known before any possible restoration action. Although an artwork cannot be considered as a composite material in which the zero-defect theory is usually followed by scientists, it is possible to state that the preservation of a multi-layered structure fabricated by the artist’s hands is based on a methodological analysis, where the use of non-destructive testing methods is highly desirable. In this paper, the infrared thermography and hyperspectral imaging methods were applied to identify both fabricated and non-fabricated targets in a canvas painting mocking up the famous character “Venus” by Botticelli. The pulse-compression thermography technique was used to retrieve info about the inner structure of the sample and low power light-emitting diode (LED) chips, whose emission was modulated via a pseudo-noise sequence, were exploited as the heat source for minimizing the heat radiated on the sample surface. Hyper-spectral imaging was employed to detect surface and subsurface features such as pentimenti and facial contours. The results demonstrate how the application of statistical algorithms (i.e., principal component and independent component analyses) maximized the number of targets retrieved during the post-acquisition steps for both the employed techniques. Finally, the best results obtained by both techniques and post-processing methods were fused together, resulting in a clear targets map, in which both the surface, subsurface and deeper information are all shown at a glance.

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