Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (7): 1-13.DOI: 10.3778/j.issn.1002-8331.2011-0341

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Overview of Image Denoising Methods Based on Deep Learning

LIU Di, JIA Jinlu, ZHAO Yuqing, QIAN Yurong   

  1. 1.College of Software, Xinjiang University, Urumqi 830046, China
    2.Key Laboratory of Signal Detection and Processing in Xinjiang Uygur Autonomous Region, Urumqi 830046, China
    3.Key Laboratory of Software Engineering, Xinjiang University, Urumqi 830046, China
  • Online:2021-04-01 Published:2021-04-02



  1. 1.新疆大学 软件学院,乌鲁木齐 830046
    2.新疆维吾尔自治区信号检测与处理重点实验室,乌鲁木齐 830046
    3.新疆大学 软件工程重点实验室,乌鲁木齐 830046


Image denoising is a kind of technology that uses the context information of image sequence to remove noise and restore clear image. It is one of the important research contents in the field of computer vision. With the development of machine learning, deep learning has been widely used in the field of image denoising, and has become an effective solution for image denoising. Firstly, the deep learning image denoising method is analyzed. Secondly, the idea of image denoising method is analyzed in detail according to the network structure, and the advantages and disadvantages are summarized. Then, through the experimental results on DND, PolyU and other data sets, the performance of deep learning based image denoising methods is compared and analyzed. Finally, the key issues of image denoising research are summarized, and the future development trend of the research of this field is discussed.

Key words: image denoising, real noise, synthetic noise, deep learning



关键词: 图像去噪, 真实噪声, 合成噪声, 深度学习