Comparative study of Video/Image denoising algorithms based on Convolutional neural network CNN

Abstract

In this paper, we present a comparative study of different algorithms used to denoise images and videos, some of them are especially used in deep neural networks so we can see the effects of its performances using different computational criteria such as PSNR and SSIM. The algorithms for image denoising are BM3D, DnCNN, FFDNet, and the others for video denoising are SPTWO, VBM4D, VNLB, DVDnet, and Fast DVDnet. The purpose of this study is to see the powerful effect of convolutional neural network CNN used in image & video denoising compared to classical techniques.