Palomero Cherry May T, Soriano Maricor N
National Institute of Physics, University of the Philippines, Diliman 1101 Quezon City, Philippines.
Opt Express. 2011 Oct 10;19(21):21011-7. doi: 10.1364/OE.19.021011.
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.
我们展示了一种新的数字清洁技术，该技术使用神经网络进行训练，以学习绘画图像从脏污部分到清洁部分的转换。该网络的输入和输出是属于费尔南多·阿莫索洛的《河畔的马拉卡南宫》中脏污和清洁部分的像素。数字清洁后，我们通过假设它是叠加在清洁后的画作上的透射滤光片来可视化画作的褪色情况。使用RGB颜色到光谱的转换来获取清洁和脏污画作图像的逐点光谱，我们计算这个“污垢”滤光片并将其渲染到整个图像上。
