Image super-resolution reconstruction based on improved K-SVD dictionary-learning

An improved super-resolution image reconstruction algorithm based on dictionary-learning is studied in order to solve the problem that the dictionary training process is time-consuming in the existing algorithms. The K-SVD dictionary alg orithm is combined with the idea that the high and low resolution dictionaries c an be co-generated. Then the high and low resolution dictionaries generated are used to the super-resolution reconstruction algorithm via sparse representation . Experiment results show that the algorithm can not only reduce the time of the dictionary training effectively, and also improve the quality of the reconstructi on of high-resolution images.