Accuracy in Colour Reproduction: Using a ColorChecker Chart to Assess the Usefulness and Comparability of Data Acquired with Two Hyper-Spectral Systems

Hyper-spectral imaging has been applied as an in situ technique for the study and accurate digital documentation of coloured artworks. Providing spectral and colorimetric characterisation across the entire surface of an object, it can be used to identify the coloured materials, measure colour changes, and document it with high fidelity. However, depending on the system used, data accuracy and reliability may vary. In this work, developed within the Round Robin Test being carried out by COSCH Working Group 1, an X-Rite® ColorChecker Classic chart was analysed with two push-broom hyper-spectral systems developed by different groups (IFAC-CNR and IP-UEF), in the 400-1000 nm range, and the data obtained were compared. This comparison allowed to assess the accuracy of colour reproduction processes performed by the two systems. The results obtained are satisfactory in terms of spectral and colorimetric accuracy for some colours, but show differences at both ends of the visible range.

[1]  Haida Liang,et al.  Advances in multispectral and hyperspectral imaging for archaeology and art conservation , 2012 .

[2]  Marcello Picollo,et al.  Extending hyperspectral imaging from Vis to NIR spectral regions: a novel scanner for the in-depth analysis of polychrome surfaces , 2013, Optical Metrology.

[3]  David Saunders.  High-quality imaging at the National Gallery: Origins, implementation and applications , 1997, Comput. Humanit..

[4]  Marcello Picollo.  A HYPER-SPECTRAL SCANNER FOR HIGH QUALITY IMAGE SPECTROSCOPY: DIGITAL DOCUMENTATION AND SPECTROSCOPIC CHARACTERIZATION OF POLYCHROME SURFACES , 2011 .

[5]  Marcello Picollo,et al.  Open issues in hyperspectral imaging for diagnostics on paintings: when high-spectral and spatial resolution turns into data redundancy , 2011, Optical Metrology.

[6]  Wencheng Wu,et al.  The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations , 2005 .

[7]  Philippe Colantoni,et al.  Analysis of multispectral images of paintings , 2006, 2006 14th European Signal Processing Conference.

[8]  Kai-Erik Peiponen,et al.  A Wide Spectral Range Reflectance and Luminescence Imaging System , 2013, Sensors.

[9]  Andrea Casini,et al.  Hyper-Spectral Acquisition on Historically Accurate Reconstructions of Red Organic Lakes , 2014, ICISP.

[10]  David Saunders,et al.  Ten years of art imaging research , 2002, Proc. IEEE.

[11]  Maria Kubik,et al.  Chapter 5 Hyperspectral Imaging: A New Technique for the Non-Invasive Study of Artworks , 2007 .

[12]  Jingge Wu.  A Color-Rendition Chart , 2017 .

[13]  R. Berns,et al.  Error propagation analysis in color measurement and imaging , 1997 .

[14]  Ioanna Kakoulli,et al.  Multispectral and hyperspectral imaging technologies in conservation: current research and potential applications , 2006 .

[15]  Frank Boochs,et al.  TOWARDS OPTIMAL SPECTRAL AND SPATIAL DOCUMENTATION OF CULTURAL HERITAGE. COSCH - AN INTERDISCIPLINARY ACTION IN THE COST FRAMEWORK , 2013 .

[16]  Liang Gao,et al.  Snapshot advantage: a review of the light collection improvement for parallel high-dimensional measurement systems , 2012, Optical engineering.

[17]  Roy S. Berns,et al.  The Science of Digitizing Paintings for Color-Accurate Image Archives : A Review , 2001 .

[18]  Claudio Oleari,et al.  Spectrophotometric Scanner for Imaging of Paintings and Other Works of Art , 2004, CGIV.