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

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 i...

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Autores principales: Laureti, Stefano, Malekmohammadi, Hamed, Rizwan, Muhammad Khalid, Burrascano, Pietro, Sfarra, Stefano, Mostacci, Miranda, Ricci, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806314/
https://www.ncbi.nlm.nih.gov/pubmed/31597266
http://dx.doi.org/10.3390/s19194335
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author Laureti, Stefano
Malekmohammadi, Hamed
Rizwan, Muhammad Khalid
Burrascano, Pietro
Sfarra, Stefano
Mostacci, Miranda
Ricci, Marco
author_facet Laureti, Stefano
Malekmohammadi, Hamed
Rizwan, Muhammad Khalid
Burrascano, Pietro
Sfarra, Stefano
Mostacci, Miranda
Ricci, Marco
author_sort Laureti, Stefano
collection PubMed
description 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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spelling pubmed-68063142019-11-07 Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography Laureti, Stefano Malekmohammadi, Hamed Rizwan, Muhammad Khalid Burrascano, Pietro Sfarra, Stefano Mostacci, Miranda Ricci, Marco Sensors (Basel) Article 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. MDPI 2019-10-08 /pmc/articles/PMC6806314/ /pubmed/31597266 http://dx.doi.org/10.3390/s19194335 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Laureti, Stefano
Malekmohammadi, Hamed
Rizwan, Muhammad Khalid
Burrascano, Pietro
Sfarra, Stefano
Mostacci, Miranda
Ricci, Marco
Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography
title Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography
title_full Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography
title_fullStr Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography
title_full_unstemmed Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography
title_short Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography
title_sort looking through paintings by combining hyper-spectral imaging and pulse-compression thermography
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806314/
https://www.ncbi.nlm.nih.gov/pubmed/31597266
http://dx.doi.org/10.3390/s19194335
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