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Super-resolution estimates a higher resolution image given a set of lower resolution images with negligible scene differences between them. There are two key techniques developed for performing the super-resolution that is discussed in this paper. First, we develop an accurate alignment algorithm for the low-resolution images that takes into account any horizontal, vertical, and rotational shifts between the set of sample images. Second, a technique for approximating a higher resolution image by using sub-pixel level basis functions is developed.