Deep Neural Network for Image Super Resolution Driven by Prior Denoising

Abstract

In order to improve image super resolution, a double layer convolution neural network in image denoising is embedded in image restoration tasks. The image super resolution method driven by prior denoising with deep neural network is proposed. The image denoising model can deal with different noise levels quickly and flexibly. The proposed image super resolution network is able to achieve image restoration. The trained network tests the low resolution images generated by bicubic down-sampling. The restored super resolution images have higher PSNR values and SSIM values than other image super resolution image methods.