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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