Recovering Intrinsic Images from a Single Image

Marshall F. Tappen, William T. Freeman, Edward H. Adelson

Advances in Neural Information Processing Systems 15 (NIPS)


We present an algorithm that uses multiple cues to recover shading and reflectance intrinsic images from a single image. Using both color information and a classifier trained to rec- ognize gray-scale patterns, each image derivative is classified as being caused by shading or a change in the surface’s reflectance. Generalized Belief Propagation is then used to propagate information from areas where the correct classification is clear to areas where it is ambiguous. We also show results on real images.