Graph-based 3D Visualization of Color Content in Paintings

Visualization of the color content of a painting can help to better understand the style, compositional structure and material content. There are several ways to visualize colorimetric data from a color image. One option consists of using of 3D Virtual Reality to view colorimetric data in arbitrary orientation in a standard color space. In this paper we propose a new colorimetric visualization method. The originality of this method is that we include spatial organization of colors inside the painting. We can thus visualize information on color gradients that may appear in the painting using simple 3D primitives. We demonstrate the efficiency of our method on a colorimetrically calibrated image of an Italian Renaissance painting.

[1]  A. Tremeau,et al.  A Gamut Preserving Color Image Quantization , 2007, 14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007).

[2]  Philippe Colantoni,et al.  GPU Spectral Viewer - A Tool for an Enhanced Colorimetric Perspective of Cultural Heritage , 2008, GRAPP.

[3]  Alain Trémeau,et al.  Image watermarking based on a color quantization process , 2007, Electronic Imaging.

[4]  Carl E. Foss Space lattice used to sample the color space of the Committee on Uniform Color Scales of the Optical Society of America , 1978 .

[5]  Ján Morovic,et al.  3D histograms in color image reproduction , 2001, IS&T/SPIE Electronic Imaging.

[6]  Philippe Colantoni,et al.  A Color Management Process for Real Time Color Reconstruction of Multispectral Images , 2009, SCIA.

[7]  David L. MacAdam,et al.  Colorimetric data for samples of OSA uniform color scales , 1978 .

[8]  Günter Wyszecki,et al.  A regular rhombohedral lattice sampling of Munsell renotation space , 1954 .

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

[10]  F. Schmitt,et al.  Studying That Smile: A tutorial on multispectral imaging of paintings using the Mona Lisa as a case study , 2008 .

[11]  Francis Schmitt,et al.  Calibration and spectral reconstruction for CRISATEL : An art painting multispectral acquisition system , 2005 .

[12]  Thierry Pun,et al.  A Stochastic Approach to Content Adaptive Digital Image Watermarking , 1999, Information Hiding.

[13]  Wencheng Wu,et al.  Mathematical Discontinuities in CIEDE2000 Color Difference Computations , 2004, Color Imaging Conference.

[14]  Alain Trémeau,et al.  3D Visualization of Color Data to Analyze Color Images , 2003, PICS.