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Comparison of Imaging Models for Spectral Unmixing in Oil Painting †

The radiation captured in spectral imaging depends on both the complex light–matter interaction and the integration of the radiant light by the imaging system. In order to obtain material-specific information, it is important to define and invert an imaging process that takes into account both aspec...

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Detalles Bibliográficos
Autores principales: Grillini, Federico, Thomas, Jean-Baptiste, George, Sony
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038140/
https://www.ncbi.nlm.nih.gov/pubmed/33918319
http://dx.doi.org/10.3390/s21072471
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author Grillini, Federico
Thomas, Jean-Baptiste
George, Sony
author_facet Grillini, Federico
Thomas, Jean-Baptiste
George, Sony
author_sort Grillini, Federico
collection PubMed
description The radiation captured in spectral imaging depends on both the complex light–matter interaction and the integration of the radiant light by the imaging system. In order to obtain material-specific information, it is important to define and invert an imaging process that takes into account both aspects. In this article, we investigate the use of several mixing models and evaluate their performances in the study of oil paintings. We propose an evaluation protocol, based on different features, i.e., spectral reconstruction, pigment mapping, and concentration estimation, which allows investigating the different properties of those mixing models in the context of spectral imaging. We conduct our experiment on oil-painted mockup samples of mixtures and show that models based on subtractive mixing perform the best for those materials.
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spelling pubmed-80381402021-04-12 Comparison of Imaging Models for Spectral Unmixing in Oil Painting † Grillini, Federico Thomas, Jean-Baptiste George, Sony Sensors (Basel) Article The radiation captured in spectral imaging depends on both the complex light–matter interaction and the integration of the radiant light by the imaging system. In order to obtain material-specific information, it is important to define and invert an imaging process that takes into account both aspects. In this article, we investigate the use of several mixing models and evaluate their performances in the study of oil paintings. We propose an evaluation protocol, based on different features, i.e., spectral reconstruction, pigment mapping, and concentration estimation, which allows investigating the different properties of those mixing models in the context of spectral imaging. We conduct our experiment on oil-painted mockup samples of mixtures and show that models based on subtractive mixing perform the best for those materials. MDPI 2021-04-02 /pmc/articles/PMC8038140/ /pubmed/33918319 http://dx.doi.org/10.3390/s21072471 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Grillini, Federico
Thomas, Jean-Baptiste
George, Sony
Comparison of Imaging Models for Spectral Unmixing in Oil Painting †
title Comparison of Imaging Models for Spectral Unmixing in Oil Painting †
title_full Comparison of Imaging Models for Spectral Unmixing in Oil Painting †
title_fullStr Comparison of Imaging Models for Spectral Unmixing in Oil Painting †
title_full_unstemmed Comparison of Imaging Models for Spectral Unmixing in Oil Painting †
title_short Comparison of Imaging Models for Spectral Unmixing in Oil Painting †
title_sort comparison of imaging models for spectral unmixing in oil painting †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038140/
https://www.ncbi.nlm.nih.gov/pubmed/33918319
http://dx.doi.org/10.3390/s21072471
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