X-ray image separation via coupled dictionary learning
  In support of art investigation, we propose a new source sepa- ration method that unmixes a single X-ray scan acquired from double-sided paintings. Unlike prior source separation meth- ods, 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. 
Nikos Deligiannis, Jo\~ao F. C. Mota, Bruno Cornelis, Miguel R. D.   Rodrigues, Ingrid Daubechies
cs.CV