Fast and Enhanced Image Inpainting with a Single- image Super-resolution Algorithm

The image processing has wide applications to deal with manipulation of digital images. There are various methods and procedures for interpreting digital images for image enhancement and restoration and performing operations on images such as blurring, zooming, sharpening, edge detection. The image restoration can also be referred as image inpainting. The image inpainting is the process which used to fill-in missing areas of the input images. This process can also be used to remove an object from the image, to restore an image. As compared to existing methods, several improvements have been done. These improvements are filling order computation and the combination of K nearest neighbours. The inpainted low -resolution image from the high-resolution input image allows to reduce computational complexity, less sensitive to noise and to work with the dominant orientations of image structures. From this inpainted low-resolution image, a single-image super-resolution is applied to reconstruct the high resolution image. The image inpainting has wide applications in digital camera and the digitalization of old photos. More than scratch removing, the image inpainting methods are also used for a text removal, an object removal and other automatic modifications of images, such as cracks in photographs or scratches and dust spots in film. It is also used to remove red eye, the stamped date from photographs.