Removing cradle artifacts in X-ray images of paintings

Published

Journal Article

© 2016 Rujie Yin. We propose an algorithm that removes the visually unpleasant effects of cradling in X-ray images of panel paintings, with the goal of improving the X-ray image readability by art experts. The algorithm consists of three stages. In the first stage the location of the cradle is detected automatically and the grayscale inconsistency, caused by the thickness of the cradle, is corrected. In a second stage we use a method called morphological component analysis to separate the X-ray image into a so-called cartoon part and a texture part, where the latter contains mostly the wood grain from both the panel and the cradling. The algorithm next learns a Bayesian factor model that distinguishes between the texture patterns that originate from the cradle and those from other components such as the panel and/or the painting on the panel surface, and finally uses this to remove the textures associated with the cradle. We apply the algorithm to a number of historically important paintings on panel. We also show how it can be used to digitally remove stretcher artifacts from X-rays of paintings on canvas. We compare our results with those obtained manually by best current practices in art conservation as well as on a ground truth dataset, consisting of X-ray images of a painting before and after removal of the physically attached cradle.

Full Text

Duke Authors

Cited Authors

  • Yin, R; Cornelis, B; Fodor, G; Ocon, N; Dunson, D; Daubechies, I

Published Date

  • August 30, 2016

Published In

Volume / Issue

  • 9 / 3

Start / End Page

  • 1247 - 1272

Electronic International Standard Serial Number (EISSN)

  • 1936-4954

Digital Object Identifier (DOI)

  • 10.1137/15M1053554

Citation Source

  • Scopus