Image inpainting using colour and gradient features
Aránzazu Jurío, Daniel Paternain, Javier Fernández, Laura De Miguel, Humberto Bustince · 2017
In this work we propose a new inpainting algorithm for color images. It is a patch-based algorithm that replicates some small areas across the image into the unknown area, in order to obtain a complete image with no visual differences between the original part and the reconstructed one. In this proposal we use color and gradient features to calculate the similarity between small windows of the image. The results show that our algorithm is able to obtain final results with better textures than the ones that only take into account the color features.