Fast and Enhanced Algorithm for Exemplar Based Image Inpainting

Abstract

Image Inpainting is the art of filling in missing data in an image. The purpose of in painting is to reconstruct missing regions in a visually plausible manner so that it seems reasonable to the human eye. There have been several approaches proposed for the same. In this paper, we present an algorithm that improves and extends a previously proposed algorithm and provides faster in painting. Using our approach, one can in paint large regions (e.g. remove an object etc.) as well as recover small portions (e.g. restore a photograph by removing cracks etc.). The in painting is based on the exemplar based approach. The basic idea behind this approach is to find examples (i.e. patches) from the image and replace the lost data with it. This technique can be used in restoring old photographs or damaged film. It can also remove superimposed text like dates, subtitles etc., or even entire objects from the image like microphones or wires to produce special effects. We obtained good quality results quickly using our approach.