1. A computer-implemented process to generate a super resolution image, the process comprising: generating a set of multi-resolution bases from one or more high-resolution training images, including extracting multiple high frequency layers and corresponding multiple middle frequency layers and extracting, from each frequency layer, image patches as bases to generate a learning Resolution-Invariant Image Representation (RIIR) basis set; receiving a low resolution image obtained by down-sampling the one or more training images; generating a multi-scale image magnification (MSIM) of the low resolution image; scaling the low resolution image either as Continuous Image Scaling (CIS) or via content-based automatic zooming; estimating a sparse resolution-invariant representation of an image at an original resolution; reconstructing the image with one or more missing patches at any resolution level including a super resolution level using the RIIR basis set; and rendering the image at the predetermined resolution level at the super resolution level higher than the original resolution.