Improvement of the visibility of concealed features in artwork NIR reflectograms by information separation

详细信息    查看全文

• 作者：Jan Blažek^a ; ^{blazek@utia.cas.cz" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Jana Striová ; ^b ; ^{jana.striova@ino.it" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Raffaella Fontana^b ; ^{raffaella.fontana@ino.it" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Barbara Zitová ; ^a ; ^{zitova@utia.cas.cz" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Signal separation ; Painted layer enhancement ; Separability limitations ; Artwork analysis ; Infrared reflectography
• 刊名：Digital Signal Processing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：60
• 期：Complete
• 页码：140-151
• 全文大小：2717 K

文摘

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 class="mathmlsrc">class="formulatext stixSupport mathImg" data-mathURL="/science?_ob=MathURL&_method=retrieve&_eid=1-s2.0-S1051200416301579&_mathId=si1.gif&_user=111111111&_pii=S1051200416301579&_rdoc=1&_issn=10512004&md5=11effc97634c14597d86da3a0e6ff51a" title="Click to view the MathML source">〈400,2250〉 nmclass="mathContainer hidden">class="mathCode">$〈400,2250〉\text{nm}$ 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.