Nonlocal mean image denoising method based on Poisson distribution

Xiao-ling GAO

doi:10.37188/YJYXS20203510.1059

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Nonlocal mean image denoising method based on Poisson distribution

Display & Image Processing | 更新时间：2020-09-28

- Nonlocal mean image denoising method based on Poisson distribution
- Chinese Journal of Liquid Crystals and Displays Vol. 35, Issue 10, Pages: 1059-1065(2020)
- 作者机构：
  
  宁夏大学新华学院, 宁夏银川 750021
- 作者简介：
- 基金信息：
  
  Scientific and Technology Research Project of Ningxia Colleges and Universities(NGY2020102)
- DOI：10.37188/YJYXS20203510.1059
  CLC： TP753
- Received：23 April 2020，
  
  Revised：20 May 2020，
  
  Accepted：20 May 2020，
  
  Published：05 October 2020
- 稿件说明：
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Xiao-ling GAO. Nonlocal mean image denoising method based on Poisson distribution[J]. Chinese journal of liquid crystals and displays, 2020, 35(10): 1059-1065.
DOI：

Xiao-ling GAO. Nonlocal mean image denoising method based on Poisson distribution[J]. Chinese journal of liquid crystals and displays, 2020, 35(10): 1059-1065. DOI： 10.37188/YJYXS20203510.1059.

摘要

针对图像去噪问题，提出基于泊松分布的非局部均值图像去噪方法。将图像中的每一个像素点建模为一个泊松分布，泊松分布的参数根据像素点非局部区域内像素值信息进行极大似然估计；两像素间的差异性由其对应泊松分布的L2范数距离计算；同时，利用两像素点邻域内点对间泊松分布的L2范数的平方和来定义其相似性权值，采用非局部均值的思想进行图像泊松去噪。实验结果表明，所提算法能很好地保留图像中的细节信息，去噪图像峰值信噪比达到22 dB以上，能够有效用于图像去噪。

Abstract

In order to handle the image denoising problem

a non-local mean image denoising method based on Poisson distribution is proposed in this paper. Each pixel in image is modeled as a poisson distribution. The parameters of Poisson distribution are estimated according to the maximum likelihood of the pixels in a non-local region. The difference between two pixels is calculated by the L2 norm distance corresponding to the Poisson distribution. Moreover

the similarity weights are defined by the sum of L2 norms between two pixels in their neighborhood points. The image Poisson denoising is carried out by using the principle of non-local mean. The experimental results show that the proposed algorithm can preserve the image details well

and the denoised image has a high peak signal-to-noise rate over 22 dB. The proposed method can be effectively used for image denoising.

关键词

Keywords

references

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