Record |
Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Anitha, A.; Brasoveanu, A.; Duarte, M.; Hughes, S.; Daubechies, I.; Dik, J.; Janssens, K.; Alfeld, M. |
Title |
Restoration of X-ray fluorescence images of hidden paintings |
Type |
A1 Journal article |
Year |
2013 |
Publication |
Signal processing |
Abbreviated Journal |
Signal Process |
Volume |
93 |
Issue |
3 |
Pages |
592-604 |
Keywords |
A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) |
Abstract |
This paper describes our methods for repairing and restoring images of hidden paintings (paintings that have been painted over and are now covered by a new surface painting) that have been obtained via noninvasive X-ray fluorescence imaging of their canvases. This recently developed imaging technique measures the concentrations of various chemical elements at each two-dimensional spatial location across the canvas. These concentrations in turn result from pigments present both in the surface painting and in the hidden painting beneath. These X-ray fluorescence images provide the best available data from which to noninvasively study a hidden painting. However, they are typically marred by artifacts of the imaging process, features of the surface painting, and areas of information loss. Repairing and restoring these images thus consists of three stages: (1) repairing acquisition artifacts in the dataset, (2) removal of features in the images that result from the surface painting rather than the hidden painting, and (3) identification and repair of areas of information loss. We describe methods we have developed to address each of these stages: a total-variation minimization approach to artifact correction, a novel method for underdetermined blind source separation with multimodal side information to address surface feature removal, and two application-specific new methods for automatically identifying particularly thick or X-ray absorbent surface features in the painting. Finally, we demonstrate the results of our methods on a hidden painting by the artist Vincent van Gogh. (C) 2012 Elsevier B.V. All rights reserved. |
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Place of Publication |
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Editor |
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Language |
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Wos |
000312521400007 |
Publication Date |
2012-10-13 |
Series Editor |
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Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0165-1684 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
Impact Factor |
3.11 |
Times cited |
13 |
Open Access |
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Notes |
; Marco F. Duarte was supported during this research by NSF Supplemental Funding DMS-0439872 to UCLA-IPAM, PI: R. Caflisch. Matthias Alfeld receives support in the form of a Ph.D. fellowship of the Research Foundation Flanders (FWO). This research was also supported by the Interuniversity Attraction Poles Programme Belgian Science Policy (IUAP VI/16). The text also presents results of GOA “XANES meets ELNES” (Research Fund University of Antwerp, Belgium) and from FWO (Brussels, Belgium) projects no. G.0704.08 and G.01769.09. ; |
Approved |
Most recent IF: 3.11; 2013 IF: 2.238 |
Call Number |
UA @ admin @ c:irua:105921 |
Serial |
5817 |
Permanent link to this record |