Overview of Image Denoising Based on Deep Learning

被引:10
|
作者
Liu, Baozhong [1 ]
Liu, Jianbin [1 ]
机构
[1] Beijing Informat Sci & Technol Univ, Sch Comp, Beijing, Peoples R China
关键词
D O I
10.1088/1742-6596/1176/2/022010
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
With the advent of the artificial intelligence era, deep learning technology is widely used in various fields, showing a good advantage in image noise reduction. In order to let more scholars understand the progress of machine learning in the field of image noise reduction, the research on machine learning in image denoising is reviewed. This paper mainly introduces three kinds of models, such as convolutional neural network, pulse coupled neural network and wavelet neural network, which are commonly used in image denoising. The nonlocal mean noise reduction method based on machine learning is described as a concrete case. The purpose of the article is to clearly understand the latest developments in deep learning in the field of image noise reduction.
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收藏
页数:6
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