Multi-scale residual network-based image restoration

Abstract

All Image restoration technology has undergone extensive research. For image degradation, inverse filtering was proposed in the last century. Then Helstrom proposed a Wiener filtering algorithm. In recent years, the convolutional neural network has promoted the further development of image restoration technology. The coarse-to-fine multi-scale residual network Multiscale Deblur Net (MDN) used in this paper is stable in operation, simple in structure, and easy to train. It has a good deblurring ability for motion-blurred images by testing in the GO_PRO dataset.