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Discovering Hidden Painted Images: Subsurface Imaging Using Microscale Spatially Offset Raman Spectroscopy.

Alessandra BotteonClaudia ContiMarco RealiniChiara ColomboPavel Matousek
Published in: Analytical chemistry (2016)
We demonstrate for the first time the mapping capability of micro-spatially offset Raman spectroscopy (micro-SORS). The technique enables to form noninvasive images of thin sublayers through highly turbid overlayers. The approach is conceptually demonstrated on recovering overpainted images in situations where conventional Raman microscopy was unable to visualize the sublayer. The specimens mimic real situations encountered in Cultural Heritage that deal, for example, with hidden paintings vandalized with graffiti or covered by superimposed painted layers or whitewash. Additionally, using a letter as a hidden image, we demonstrated the micro-SORS potential to reconstruct also a hidden writing covered, for example, with paper sheets that cannot be easily removed. Potential applications could also include other disciplines such as polymers, biological, catalytic, and forensic sciences where thin, highly turbid layers mask chemically distinct subsurface structures.
Keyphrases
  • raman spectroscopy
  • deep learning
  • high resolution
  • optical coherence tomography
  • convolutional neural network
  • human health
  • machine learning
  • risk assessment
  • single molecule
  • obstructive sleep apnea
  • climate change