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.

Keywords: Inpainting · Image completion · Hole filling ·
Particle filter · Markov random field