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Article

Comparison of Imaging Models for Spectral Unmixing in Oil Painting †

The Norwegian Colour and Visual Computing Laboratory, Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, Norway
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in Grillini, F.; Thomas, J.B.; George, S. Mixing models in close-range spectral imaging for pigment mapping in cultural heritage. Proceedings of the International Colour Association (AIC) Conference 2020, 2020, pp. 372–376, and in Grillini, F.; Thomas, J.B.; George, S. Linear, Subtractive and Logarithmic Optical Mixing Models in Oil Painting. Proceedings of the 10th Colour and Visual Computing Symposium. Gjøvik, Norway, 2020.
Academic Editor: Eva M. Valero Benito
Sensors 2021, 21(7), 2471; https://doi.org/10.3390/s21072471
Received: 24 March 2021 / Revised: 29 March 2021 / Accepted: 30 March 2021 / Published: 2 April 2021
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. View Full-Text
Keywords: spectral imaging; imaging models; spectral unmixing; pigment mapping spectral imaging; imaging models; spectral unmixing; pigment mapping
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MDPI and ACS Style

Grillini, F.; Thomas, J.-B.; George, S. Comparison of Imaging Models for Spectral Unmixing in Oil Painting. Sensors 2021, 21, 2471. https://doi.org/10.3390/s21072471

AMA Style

Grillini F, Thomas J-B, George S. Comparison of Imaging Models for Spectral Unmixing in Oil Painting. Sensors. 2021; 21(7):2471. https://doi.org/10.3390/s21072471

Chicago/Turabian Style

Grillini, Federico, Jean-Baptiste Thomas, and Sony George. 2021. "Comparison of Imaging Models for Spectral Unmixing in Oil Painting" Sensors 21, no. 7: 2471. https://doi.org/10.3390/s21072471

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