Single image super resolution based on sparse representation and adaptive dictionary selection

摘要

An improved single image super resolution based on patch-wise sparse recovery is proposed in this paper. K-SVD is adopted to train a coupled dictionary. Besides, adaptive selection is proposed among dictionaries with different patch size. Simulation results show that the proposed approach provides good subjective quality and up to 0.4 dB PSNR improvement with significant time reduction.