A Review of Convolutional Neural Network based Image Denoising Algorithms

Mengke Wang

doi:10.4108/eetel.v8i3.3461

Authors

Mengke Wang Henan Polytechnic University

DOI:

https://doi.org/10.4108/eetel.v8i3.3461

Keywords:

Convolutional neural network, Denoising Algorithms, Image Processing, Deep Learning

Abstract

Currently, image-denoising algorithms based on convolutional neural networks (CNN) have been widely used and have achieved good results. Compared with traditional image-denoising methods, it has powerful learning ability and efficient algorithms. This paper summarizes traditional denoising methods and CNN-based image denoising methods, and introduces the basics of image denoising in detail, which is helpful for readers who are starting with image denoising processing. In addition, this paper also summarizes some commonly used datasets in the field of image processing, which makes it easier for us to denoise images. Finally, some suggestions for improving the performance of CNN image denoising are presented, and possible future research directions are discussed.

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