A smarter exemplar-based inpainting algorithm using local and global heuristics for more geometric coherence

In this paper, we propose two major improvements to the exemplar-based image inpainting algorithm, initially formulated by Criminisi et al. [1]. First, we introduce a structure-tensor-based data-term for a better selection of pixel candidates to fill in based on priority. Then, we propose a new lookup heuristic in order to locate the best source patches to copy/paste to these targeted points. These two contributions clearly make the inpainting algorithm reconstruct more geometrically coherent images, as well as speed up the process drastically. We illustrate the great performances of our approach compared to existing state-of-the-art methods.