CULTURAL HERITAGE
Tracing of the lines relating to underdrawings for the first composition, incorporating information from all technical images
Figure 2: Detail from hyperspectral imaging data, which also revealed the drawing of the angel and baby of the first composition (under the landscape at the right side of the painting)
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hyperspectral camera that uses a grating spectrometer with a 30µm width slit for wavelength dispersion. An intermediate relay lens projects the dispersed spatial line onto a 1,280 x 1,024-pixel InSb detector, providing a 3nm spectral sampling interval and 500 spectral bands. Te area under study was illuminated with two 125W halogen lamps controlled by a rheostat. Under the working conditions used for
studying the painting, the optics of the system provided a field of view of about 21cm. Since the painting measures 189.5 x 120cm, 11 scans were required to cover its entire surface. Each scan included a 15 per cent region of overlap to be able to mosaic the whole surface. Te scans were acquired by moving the painting – installed on a computer- controlled micro-positioning easel – and keeping the camera static. With an integration time of 100ms for image acquisition, each of the 11 hyperspectral datacubes took 15 minutes to generate. Hyperspectral imaging is a powerful
technique that provides the best performance after spectral data treatment. Te raw data sets were flat-field corrected with a white Labsphere Spectralon diffuse reflectance target panel (99 per cent), darkfield corrected, and calibrated with a black and a white standard, which were included in the field of view at the acquisition time. To recreate the entire surface, the 11 scans
were mosaiced together. Te interpretation of the data was performed by visualising
‘Te false-colour image highlights differences in materials that otherwise could not be seen’
single-band images and creating false-colour images, assigning to the red, green and blue channels three spectral bands of interest; the false-colour image highlights differences in the painting materials that otherwise could not be seen. Another approach to identify interesting
features relative to the spectral behaviour of the materials is to apply chemometrics, in this case principal component (PC) and minimum noise fraction (MNF) transforms. Dr Marta Melchiorre, who performed the analysis, found that MNF was particularly effective in providing images with improved signal-to-noise ratio, which highlighted features not visible in the original images. Figure two shows one of the eigen images resulting from the MNF transform, and highlights the traces of the angel and the child outlines, matching with the zinc map (figure one).
Te strength of hyperspectral imaging
goes beyond making the invisible visible. Te possibility to extract reflectance spectra from each pixel of the image allows pigments to be identified, complementing XRF results. For example, it is possible to identify a copper- based blue as azurite.
6 IMAGING AND MACHINE VISION EUROPE FEBRUARY/MARCH 2020
To be continued... Imaging techniques are a suitable and effective approach to investigate pieces of art, allowing the study of a work in a non-invasive and non-destructive manner. Te research done by Dr Marta Melchiorre and colleagues at the National Gallery shows how hyperspectral imaging can reveal hidden underdrawings made in the early creation stages. Te imaging method can also identify the composition and map materials over the surface of the painting, saving time compared to point-by-point spectroscopic techniques. Te evolution of hyperspectral imaging
means that more meaningful data can be collected, compared to older methods such as infrared reflectography, providing a deeper understanding of the painting. Te possibility to process the spectral data with multivariable statistics gives information that goes beyond the appearance of the image. As an ongoing project, further analysis of the data could still reveal more. Finally, the interpretation of findings is
ongoing and further work is planned to fully understand the results in the historical context of this painting. O
Acknowledgements Te author would like to thank Dr Marta Melchiorre, Dr Catherine Higgitt and Marika Spring from the National Gallery’s scientific department for the support and time dedicated to providing an insight into da Vinci’s work.
About the author
Dr Giorgia Marucci is an applications specialist working in the spectroscopy and spectral imaging team at Pro-Lite Technology, a supplier of specialist equipment and services with a technical focus in photonics. For further details, visit
www.pro-lite.co.uk
@imveurope |
www.imveurope.com
The National Gallery, London
The National Gallery, London
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