Digital Cultural Heritage imaging via osmosis filtering
For conservators and cultural heritage professionals, it provides a computational method to enhance diagnostic imaging, but the approach is an application of an existing model to a new domain.
The paper applies an osmosis filtering model to correct intensity inhomogeneities and integrate multi-modal images in cultural heritage imaging, demonstrating effectiveness on real datasets including thermal measurements of a Da Vinci mural, UV-VIS-IR imaging of an icon, and the Archimedes Palimpsest.
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.