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Journal Publication

Multi-Modal Dictionary Learning for Image Separation With Application In Art Investigation

This publication appears in: IEEE Transactions on Image Processing

Authors: N. Deligiannis, J. Mota, B. Cornelis, M. Rodrigues and I. Daubechies

Volume: 26

Issue: 2

Pages: 751-764

Publication Date: Feb. 2017


Abstract:

In support of art investigation, we propose a new
source separation method that unmixes a single X-ray scan
acquired from double-sided paintings. In this problem, the X-ray
signals to be separated have similar morphological characteristics,
which brings previous source separation methods to their
limits. Our solution is to use photographs taken from the frontand
back-side of the panel to drive the separation process. The
crux of our approach relies on the coupling of the two imaging
modalities (photographs and X-rays) using a novel coupled
dictionary learning framework able to capture both common
and disparate features across the modalities using parsimonious
representations the common component captures features shared
by the multi-modal images, whereas the innovation component
captures modality-specific information. As such, our model
enables the formulation of appropriately regularized convex
optimization procedures that lead to the accurate separation of
the X-rays. Our dictionary learning framework can be tailored
both to a single- and a multi-scale framework, with the latter
leading to a significant performance improvement. Moreover, to
improve further on the visual quality of the separated images,
we propose to train coupled dictionaries that ignore certain parts
of the painting corresponding to craquelure. Experimentation on
synthetic and real data—taken from digital acquisition of the
Ghent Altarpiece (1432)—confirms the superiority of our method
against the state-of-the-art morphological component analysis
technique that uses either fixed or trained dictionaries to perform
image separation.

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Prof. Dr. Ir. Nikolaos Deligiannis

+32 (0)02 629 168

ndeligia@etrovub.be

more info

Dr. Ir. Bruno Cornelis

+32 (0)02 629 167

bcorneli@etrovub.be

more info

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