Exploration into Single Image Super-Resolution via Self Similarity by Sparse Representation
Lv Guo, Yin Li, Jie Yang, Li Lü · IEICE Transactions on Information and Systems · 2010
A novel method for single image super resolution without any training samples is presented in the paper. By sparse representation, the method attempts to recover at each pixel its best possible resolution increase based on the self similarity of the image patches across different scale and rotation transforms. The experiments indicate that the proposed method can produce robust and competitive results.