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Proceedings Paper

After digital cleaning: visualization of the dirt layer
Author(s): Cherry May T. Palomero; Maricor N. Soriano
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Paper Abstract

Completely non-invasive digital cleaning of Fernando Amorsolo's 1948 oil on canvas, Malacañang by the River, is implemented using a trained neural network. The digital cleaning process results to more vivid colors and a higher luminosity for the digitally-cleaned painting. We propose three methods for visualizing the color change that occurred to a painting image after digital cleaning. For the first two visualizations, the color change between original and digitally-cleaned image is computed as a vector difference in RGB space. For the first visualization, the vector difference is projected on a neutral color and rendered for the whole image. The second visualization renders the color change as a translucent dirt layer that can be superimposed on a white image or on the digitally-cleaned image. For the third visualization, we model the color change as a dirt layer that acts as a filter on the painting image. The resulting color change and dirt layer visualizations are consistent with the actual perceived color change and could offer valuable insights to a painting's color changing process due to exposure.

Paper Details

Date Published: 8 March 2011
PDF: 7 pages
Proc. SPIE 7869, Computer Vision and Image Analysis of Art II, 78690O (8 March 2011); doi: 10.1117/12.876662
Show Author Affiliations
Cherry May T. Palomero, Univ. of the Philippines (Philippines)
Maricor N. Soriano, Univ. of the Philippines (Philippines)


Published in SPIE Proceedings Vol. 7869:
Computer Vision and Image Analysis of Art II
David G. Stork; Jim Coddington; Anna Bentkowska-Kafel, Editor(s)

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