Automated digital color restitution of mural paintings using minimal art historian input

Abstract

Digital color restitution aims to digitally restore the original colors of a painting. Existing image editing applications can be used for this purpose, but they require a select-and-edit workflow and thus they do not scale well to large collections of paintings or different regions of the same painting. To address this issue, we propose an automated workflow that requires only a few representative source colors and associated target colors as input from art historians. The system then creates a control grid to model a deformation of the CIELAB color space. Such deformation can be applied to arbitrary images of the same painting. The proposed approach is suitable for restituting the color of images from a large photographic campaign, as well as for the textures of 3D reconstructions of a monument. We demonstrate the benefits of our method on a collection of mural paintings from a medieval monument.

This work has been partially supported by projects PID2021-122136OB-C21 and PID2021-122136OB-C22 funded by MCIN/AEI/ 10.13039/501100011033 and by ERDF A way of making Europe, by the EU Horizon 2020, JPICH Conservation, Protection and Use initiative (JPICH-0127) and the Spanish Agencia Estatal de Investigación (grant PCI2020-111979).

Peer Reviewed

Postprint (published version)