Field of Particle Filters for Image Inpainting

We present a novel algorithm for solving the image inpainting problem based on a field of locally interacting particle filters. Image inpainting, also known as image completion, is concerned with the problem of filling image regions with new visually plausible data. In order to avoid the difficulty of solving the problem globally for the region to be inpainted, we introduce a field of local particle filters. The states of the particle filters are image patches. Global consistency is enforced by a Markov random field image model which connects neighbouring particle filters. The benefit of using locally interacting particle filters is that several competing hypotheses on inpainting solutions are kept active, allowing the method to provide globally consistent solutions on problems where other local methods may fail. We provide examples of applications of the developed method.