Region Filling and Object Removal by Exemplar Based Image Inpainting

Image Inpainting is the art of restoring lost parts of image by reconstructing them using background information. Recently various approaches have been proposed. In the past, this problem has been addressed by two classes of algorithms: (i) “Texture Synthesis� algorithms for generating large image regions from sample textures, and (ii) “Structure Propagation� techniques for filling in small image gaps. In this paper we are providing an effective algorithm that contains the advantages of above two methods. The exemplar-based texture synthesis contains the essential process required to replicate both texture and structure. The existing algorithms are combined to improve the efficiency for finding the line association in selected region. Data term and confidence term are used to calculate the patch priority. With the help of priority term region filling is done that defines filling order of patches in the image. A number of examples on real and synthetic images demonstrate the effectiveness of our algorithm in removing large occluding objects as well as thin scratches.