X-ray image separation via coupled dictionary learning
Conference Paper
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