1. A method for performing image recovery comprising: generating, using at least one processor, an ensemble of sparse models from uncorrupted training data; using respective sparse models of the ensemble of sparse models to generate a plurality of individual approximations of a first image, wherein each individual approximation of the plurality of individual approximations corresponds to a particular sparse model of the respective sparse models; and aggregating, using the at least one processor, the individual approximations to generate a second image.