X-ray image separation via coupled dictionary learning

Published

Conference Paper

© 2016 IEEE. In support of art investigation, we propose a new source separation method that unmixes a single X-ray scan acquired from double-sided paintings. Unlike prior source separation methods, which are based on statistical or structural incoherence of the sources, we use visual images taken from the front- and back-side of the panel to drive the separation process. The coupling of the two imaging modalities is achieved via a new multi-scale dictionary learning method. Experimental results demonstrate that our method succeeds in the discrimination of the sources, while state-of-the-art methods fail to do so.

Full Text

Duke Authors

Cited Authors

  • Deligiannis, N; Mota, JFC; Cornelis, B; Rodrigues, MRD; Daubechies, I

Published Date

  • August 3, 2016

Published In

Volume / Issue

  • 2016-August /

Start / End Page

  • 3533 - 3537

International Standard Serial Number (ISSN)

  • 1522-4880

International Standard Book Number 13 (ISBN-13)

  • 9781467399616

Digital Object Identifier (DOI)

  • 10.1109/ICIP.2016.7533017

Citation Source

  • Scopus