Improvement of the visibility of concealed features in artwork NIR reflectograms by information separation
Authors: Blazek J., Striova J., Fontana R., Zítová B.
Autors Affiliation: Institute of Information Theory and Automation of the CAS,Prague, Czech Republic; National Institute of Optics, National Research Council, Largo Fermi 6, 50125, Florence, Italy
Abstract: Near Infrared (NIR) reflectography, coupled to visible (VIS) one, is a spectrophotometric imaging technique employed to probe both the inner and the outer layers of artworks. NIR reflectograms may partially contain information pertinent to the visible spectrum (due to the poor pigment transparency in NIR) and this decreases their comprehensibility. This work presents an innovative digital processing methodology for accentuating information contained in the infrared reflectograms. The proposed method consists of inducing minor changes in pixel intensity by suppressing VIS information content from NIR information content. The method creates such enhanced NIR reflectogram by extrapolating VIS reflectogram to a reflectogram recorded in NIR range and by subtracting it from the measured values in the near infrared spectral sub-band. As an extrapolator we suggest a feed forward artificial neural network (ANN). Significant results of improved visualization are exemplified on reflectograms acquired with a VIS-NIR (400, 2250) nm scanning device on real paintings such as Madonna dei Fusi attributed to Leonardo da Vinci. Parameters of the method, artificial neural network and separability of used pigments are discussed. (C) 2016 Elsevier Inc. All rights reserved.
Journal/Review: DIGITAL SIGNAL PROCESSING
Volume: 60 Pages from: 140 to: 151
More Information: We would like to thank to Janka Hradilová and Blanka Valchárová for the possibility capture photos presented in Fig. 9 . Access to computing and storage facilities owned by parties and projects contributing to the National Grid Infrastructure MetaCentrum, provided under the programme “Projects of Large Infrastructure for Research, Development, and Innovations” (LM2010005), is greatly appreciated. Without them this research cannot be possible. The authors of INO would like to acknowledge the INSIDDE project (INtegration of cost-effective Solutions for Imaging, Detection, and Digitisation of hidden Elements in paintings), FP7-ICT-2011.8.2 ICT for access to cultural resources. Moreover, we thank Dr. Marta Florez Igual from the Museo de Bellas Artes de Asturias for providing us with the painting shown in Fig. 10 . The authors of IITA CAS would like to acknowledge the Czech Science Foundation , which has supported this work (project no. P103/12/2211 ).KeyWords: Imaging techniques; Neural networks, Artwork analysis; Feed-forward artificial neural networks; Information separation; Infrared reflectograms; Infrared reflectography; Near infrared spectral; Separability limitations; Signal separation, Infrared devicesDOI: 10.1016/j.dsp.2016.09.007Citations: 5data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2021-10-24References taken from IsiWeb of Knowledge: (subscribers only)Connecting to view paper tab on IsiWeb: Click hereConnecting to view citations from IsiWeb: Click here