Research on image super-resolution based on attention mechanism and multi-scale
Xiaokang Ren, Xingzhen Li · Journal of Physics Conference Series · 2021
Abstract In order to solve the problem of the single feature scale of the generated image in the SISR field and the lack of texture information, a parallel generation confrontation network structure based on the attention mechanism and multi-scale is proposed on the basis of SRGAN, which adopts a dual generator and discriminator combined with attention module model. Train the network to learn multi-scale features, and integrate high-frequency information of different scales in the residual network. The experimental results on Set5, Set14, and BSD100 benchmark data sets prove that the algorithm has a good effect in restoring image detail information.