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Updated: Nov 7, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
Published on: June 18, 2021
Comparison of Imaging Models for Spectral Unmixing in Oil Painting
Federico Grillini1, Jean-Baptiste Thomas1, Sony George1
1The Norwegian Colour and Visual Computing Laboratory, Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, Norway.
Abstract:
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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