Motion blur image restoration based on generative adversarial networks
Feng Wang, Qiong Cai · 2022
During the image capture process, it is difficult to maintain relative stillness between the camera and the subject, resulting in blurred images. In order to solve this problem, based on the generative adversarial network, this paper introduces a residual module to solve the gradient dispersion problem generated during the training process. The multi-scale theory is introduced to process the image to better extract the detailed information of the image. Finally, the experiment shows that the scheme has achieved good results.