Digital Cultural Heritage imaging via osmosis filtering

TL;DR

This paper applies the osmosis filtering model to improve the analysis of multi-spectral cultural heritage images, addressing intensity inhomogeneities and enhancing information transfer across modalities for better artifact inspection.

Contribution

It introduces the use of the osmosis model with stable operator splitting techniques for processing complex cultural heritage imaging data.

Findings

Effective correction of intensity inhomogeneities in real artwork datasets.

Improved integration of multi-modal imaging information.

Demonstrated applicability on diverse cultural heritage artifacts.

Abstract

In Cultural Heritage (CH) imaging, data acquired within different spectral regions are often used to inspect surface and sub-surface features. Due to the experimental setup, these images may suffer from intensity inhomogeneities, which may prevent conservators from distinguishing the physical properties of the object under restoration. Furthermore, in multi-modal imaging, the transfer of information between one modality to another is often used to integrate image contents. In this paper, we apply the image osmosis model proposed in (Weickert et al. 2013) to solve similar problems arising when using diagnostic CH imaging techniques based on reflectance, emission and fluorescence mode in the optical and thermal range. For an efficient computation, we use stable operator splitting techniques. We test our methods on real artwork datasets: the thermal measurements of the mural painting "Monocromo" by Leonardo Da Vinci, the UV-VIS-IR imaging of an ancient Russian icon and the Archimedes Palimpsest dataset.