Smart interpolation by anisotropic diffusion

To enlarge a digital image from a single frame preserving the perceptive cues is a relevant research issue. The best known algorithms take into account the presence of edges in the luminance channel, to interpolate correctly the samples/pixels of the original image. This approach allows the production of pictures where the interpolated artifacts (aliasing blurring effect,...) are limited but where high frequencies are not properly preserved. The zooming algorithm proposed in this paper on the other hand reduces the noise and enhances the contrast to the borders/edges of the enlarged picture using classical anisotropic diffusion improved by a smart heuristic strategy. The method requires limited computational resources and it works on gray-level images, RGB color pictures and Bayer data. Our experiments show that this algorithm outperforms in quality and efficiency the classical interpolation methods (replication, bilinear, bicubic).