Learning-based Super-resolution Technique

Learning-based super-resolution technique predicts the high-resolution images from the input low-resolution ones, through learningfrom a training set which consists of a large number of other high-resolution images. And the results are better than the reconstruction basedsuper-resolution algorithms. The related work, theory and algorithms of learning-based super-resolution are illustrated. The crucial problems whichneed to be resolved in further work are proposed. Directions of future research are pointed.