Digital cleaning and "dirt" layer visualization of an oil painting.

We demonstrate a new digital cleaning technique which uses a neural network that is trained to learn the transformation from dirty to clean segments of a painting image. The inputs and outputs of the network are pixels belonging to dirty and clean segments found in Fernando Amorsolo's Malacañang by the River. After digital cleaning we visualize the painting's discoloration by assuming it to be a transmission filter superimposed on the clean painting. Using an RGB color-to-spectrum transformation to obtain the point-per-point spectra of the clean and dirty painting images, we calculate this "dirt" filter and render it for the whole image.