Abstract: ImageInpainting is the process of reconstructing lost or deteriorated part of images based on thebackground information.This paper introduces a novel framework for exemplar-based inpainting. It consists in performing first the inpainting on a coarse version of the input image. A super-resolution algorithm is then used to recover details on the missing areas. The advantage of this approach is that it is easier to inpaint low-resolution pictures than high-resolution ones. The gain is both in terms of computational complexity and visual quality. However, to be less sensitive to the parameter setting of the inpainting method, the low-resolution input picture is inpainted several times with different configurations. Results are efficiently combined with loopy belief propagation and details are recovered by a single-image super-resolution algorithm. Experimental results in a context of image editing and texture synthesis demonstrate the effectiveness of the proposed method.
Keywords: Image inpainting, super resolution inpainting, Low-resolution, High Resolution, exemplar-based inpainting.