X-ray image separation via coupled dictionary learning

Nikos Deligiannis, João F. C. Mota, Bruno Cornelis, Miguel Raul Dias Rodrigues, Ingrid Daubechies

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)


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.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
Number of pages5
ISBN (Electronic)9781467399616
Publication statusPublished - Aug 2016
Event23rd IEEE International Conference on Image Processing - Phoenix Convention Center, Phoenix, United States
Duration: 25 Sept 201628 Sept 2016


Conference23rd IEEE International Conference on Image Processing
Abbreviated titleICIP 2016
Country/TerritoryUnited States


  • Dictionary learning
  • Image decomposition
  • Image separation
  • Multi-modal imaging
  • Side information

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


Dive into the research topics of 'X-ray image separation via coupled dictionary learning'. Together they form a unique fingerprint.

Cite this