Image inpainting based on local optimisation

In this paper, we tackle the problem of image inpainting which aims at removing objects from an image or repairing damaged pictures by replacing the missing regions using the information in the rest of the scene. The image inpainting method proposed here builds on an exemplar-based perspective so as to improve the local consistency of the inpainted region. This is done by selecting the optimal patch which maximises the local consistency with respect to abutting candidate patches. The similarity computation generates weights based upon an edge prior and the structural differences between inpainting exemplar candidates. This treatment permits the generation of an inpainting sequence based on a list of factors. The experiments show that the proposed method delivers a margin of improvement as compared to alternative methods.