Automatic registration and mosaicking of technical images of Old Master paintings

Abstract

The registration of technical art conservation images of Old Master paintings presents unique challenges. Specifically, X-radiographs and reflective infrared (1000–2500 nm) images reveal shifted, or new, compositional elements not visible on the surface of artworks. Here, we describe a new multimodal registration and mosaicking algorithm that is capable of providing accurate alignment of a variety of types of images, such as the registration of multispectral reflective infrared images, X-radiographs, hyperspectral image cubes, and X-ray fluorescence image cubes to reference color images taken at high spatial sampling (300–500 pixels per inch), even when content differences are present, and a validation study has been performed to quantify the algorithm’s accuracy. Key to the algorithm’s success is the use of subsets of wavelet images to select control points and a novel method for filtering candidate control-point pairs. The algorithm has been used to register more than 100 paintings at the National Gallery of Art, D.C. and The Art Institute of Chicago. Many of the resulting registered datasets have been published in online catalogues, providing scholars additional information to further their understanding of the paintings and the working methods of the artists who painted them.