Amplifying — or removing — visual variation
At the Siggraph Asia conference this week, MIT researchers presented a pair of papers describing techniques for either magnifying or smoothing out small variations in digital images. The techniques could be used to produce more polished images for graphic-design projects, or, applied in the opposite direction, they could disclose structural defects, camouflaged objects, or movements invisible to the naked eye that could be of scientific interest. Conceptually, the work builds on a long line of research from several groups in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), which sought to amplify minute motions in digital video. “In motion magnification, the deviations are over time, and the model is deviation from being perfectly static,” says Tali Dekel, a postdoc in CSAIL and a co-author on both papers. “Our method takes as input only a single image, and it looks for deviation in space. We don’t need to know time history to do...