8 March 2011 After digital cleaning: visualization of the dirt layer
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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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cherry May T. Palomero, Cherry May T. Palomero, Maricor N. Soriano, Maricor N. Soriano, } "After digital cleaning: visualization of the dirt layer", Proc. SPIE 7869, Computer Vision and Image Analysis of Art II, 78690O (8 March 2011); doi: 10.1117/12.876662; https://doi.org/10.1117/12.876662

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