Learning the 2-D Topology of Images

We study the following question: is the two-dimensional structure of images a very strong prior or is it something that can be learned with a few examples of natural images? If someone gave us a learning task involving images for which the two-dimensional topology of pixels was not known, could we discover it auto- matically and exploit it? For example suppose that the pixels had been permuted in a x ed but unknown way, could we recover the relative two-dimensional loca- tion of pixels on images? The surprising result presented here is that not only the answer is yes but that about as few as a thousand images are enough to approxi- mately recover the relative locations of about a thousand pixels. This is achieved using a manifold learning algorithm applied to pixels associated with a measure of distributional similarity between pixel intensities. We compare different topology- extraction approaches and show how having the two-dimensional topology can be exploited.