Image interpolation using classification and stitching
Image interpolation is a well-studied signal processing application that continues to receive substantial attention from the research community. It has been recognized that taking into account the presence of edges in an image can significantly improve the resulting interpolated image. Many techniques modify the interpolation method in the presence of edges to avoid common artifacts such as blurring, blocking and ringing. We propose to improve upon this idea by fusing the best features of several interpolation methods. This can be done using a novel region classification algorithm to determine which method is best suited to a particular region. From this information, we can use image mosaic techniques to fuse the methods into a result that contains both sharp edges and detailed textures.