*2.2. Sparse-Coding-Based Network (SCN)*

The SCN method [9] firstly obtains the sparse prior information of the image through the feature extraction layer, then establishes a feed-forward neural network which can implement sparse encoding and decoding of the image, and finally uses a cascade network to complete the image enlargement. This method can improve the Peak Signal-to-Noise Ratio (PSNR) at a higher magnification, and the algorithm running speed is further improved. Moreover, with the correct understanding of each layer's physical meaning, the SCN method offers a more principled way to initialize the parameters, which helps to improve optimization speed and quality.
