Paper
20 February 2012 Mapping colors from paintings to tapestries: rejuvenating the faded colors in tapestries based on colors in reference paintings
Marie Ström, Eija Johansson, David G. Stork
Author Affiliations +
Proceedings Volume 8291, Human Vision and Electronic Imaging XVII; 82911F (2012) https://doi.org/10.1117/12.905275
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
We addressed the problem of recovering or "rejuvenating" colors in a faded tapestry (the target image) by automatically mapping colors from digital images of the reference painting or cartoon (the source image). We divided the overall computational challenge into several subproblems, and implemented their solutions in Matlab: 1) quantizing the colors in both the tapestry and the referent painting, 2) matching corresponding regions in the works based on spatial location, area and color, 3) mapping colors from regions in the source image to corresponding regions in the target image, and 4) estimating the fading of colors and excluding color mapping of areas where color has not faded. There are a number of semi-global design parameters in our algorithm, which we currently set by hand, for instance the parameter that balance the effects of 1) matching color areas in the two images and 2) matching the spatial locations between the two images. We demonstrated our method on synthetic data and on small portions of 16th-century European tapestries of cultural patrimony. Our first steps in a proof-of-concept work suggest that future refinements to our method will lead to a software tool of value to art scholars.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marie Ström, Eija Johansson, and David G. Stork "Mapping colors from paintings to tapestries: rejuvenating the faded colors in tapestries based on colors in reference paintings", Proc. SPIE 8291, Human Vision and Electronic Imaging XVII, 82911F (20 February 2012); https://doi.org/10.1117/12.905275
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KEYWORDS
Reconstruction algorithms

Digital imaging

Detection and tracking algorithms

Image restoration

Algorithm development

Colorimetry

Image segmentation

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