Single image super-resolution using global enhanced upscale network

Current works on super-resolution have obtained satisfactory results since the advance of the convolution neural network. Nevertheless, most previous works use one network for one integer scale factor so ignore the super-resolution of the arbitrary scale factor. In this work, we propose a novel approach called Global Enhanced Upscale Network (GEUN) to tackle super-resolution with a single model adapting the arbitrary scale factor. In our GEUN, we propose the Global Enhanced Upscale module to replace the conventional upscale module. Our GEUN can upscale low-resolution images with an arbitrary scale factor through only one model. Extensive experimental results demonstrate the superiority of our GEUN.