Super-resolution reconstruction based on two-stage residual neural network

With the constant update of deep learning technology, super-resolution reconstruction technology based on has also attained a significant breakthrough. This paper primarily discusses integration and techniques. Regarding application in reconstruction, improvement is focused two dimensions algorithm efficiency effect. On basis currently available neural network algorithms, this puts forward two-stage residual structure. Thereinto, mainly embodied modification image feature extraction modules increase block into stages. It experimentally evidenced by simulation that shows certain extent for effect compared with related methods.