Multiple Image Inpainting Framework with Super-Resolution

ABSTRACT- This paper introduces a replacement examplar-based inpainting frame-work. a rough version of the input image is initial inpainted by a non-parametric patch sampling. Compared to existing approaches, some enhancements are done (e.g. filling order computation, combination of K nearest neighbours). The inpainted of a rough version of the input image permits to scale back the procedure quality, to be less sensitive to noise and to figure with the dominant orientations of image structures. From the low-resolution inpainted image, a single-image moreover as multiple-image super-resolution is applied to recover the missing areas. Experimental results on natural pictures and texture synthesis demonstrate the activeness of the proposed technique.