Comparison of Imaging Models for Spectral Unmixing in Oil Painting

Sensors (Basel). 2021 Apr 2;21(7):2471. doi: 10.3390/s21072471.

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.

Keywords: imaging models; pigment mapping; spectral imaging; spectral unmixing.