Multimodal image registration and mosaicking of artworks: an approach based on mutual information

Abstract

We present an automated method for registration and mosaicking of multimodal technical images of artworks based on mutual information. We focus on the registration of element distribution maps resulting from macro X-ray fluorescence (MA-XRF) scanning, which can be considered as a layered stack and treated as the moving image. The target fixed image is the visible image of the same artwork. In consecutive stages, a unique, optimised transformation that provides the highest average mutual information across all images in the stack is identified with consensus. This transformation can be applied to the moving image to obtain the best alignment between the moving and fixed images when overlapped.