Noise detection and image denoising based on fractional calculus

2020 ◽  
Vol 131 ◽  
pp. 109463 ◽  
Author(s):  
Qi Wang ◽  
Jing Ma ◽  
Siyuan Yu ◽  
Liying Tan
Keyword(s):  
Fractional Calculus ◽  
Image Denoising ◽  
Noise Detection

scholarly journals Image denoising based on noise detection

2018 ◽  
Vol 322 ◽  
pp. 072050
Author(s):  
Yuanxiang Jiang ◽  
Rui Yuan ◽  
Yuqiu Sun ◽  
Jinwen Tian
Keyword(s):  
Image Denoising ◽  
Noise Detection

Study on the Algorithm Based on Local Correlation for Noise Detection

2014 ◽  
Vol 971-973 ◽  
pp. 1764-1767
Author(s):  
Li Hua Sun ◽  
En Liang Zhao ◽  
Qi Cheng Xu
Keyword(s):  
Image Denoising ◽  
Heat Conduction Equation ◽  
Numerical Experiments ◽  
Impulse Noise ◽  
Median Filtering ◽  
Noise Detection ◽  
Local Correlation ◽  
Noise Point ◽  
Mixed Noise ◽  
Image Details

This paper presents a new method for removing mixed noise based on the local correlation and local correlation for removal of center in the image. We can distinguish between the signal point and impulse noise point. We will process the impulse noise point using the median filtering, and the signal point will be preserved. The image for removal of impulse noise after the transition is filtered by Gauss noise based on the heat conduction equation in image denoising algorithm. The numerical experiments show the clearer image may be obtained by the proposed method for image denoising. The denoising image retains the image details. It is an effective method for image denoising.

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