Example-based super-resolution for enhancing spatial resolution of medical images.

This paper proposes an effective exampled-based super-resolution (SR) method to improve the spatial resolution of medical image heavily corrupted by noise. Based on the sparsity of patches, the reconstruction of a high-resolution (HR) patch from each low-resolution (LR) input patch can be performed with the help of a database, by solving a non-negative sparse optimization problem. The challenge is to effectively solve this problem in case of a large size database.