Salt and pepper noise filtering algorithm based on connectivity detection

Yi-dong MA; Shun-yong ZHOU

doi:10.3788/YJYXS20203502.0167

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Salt and pepper noise filtering algorithm based on connectivity detection

Image Processing | 更新时间：2020-07-16

- Salt and pepper noise filtering algorithm based on connectivity detection
- Chinese Journal of Liquid Crystals and Displays Vol. 35, Issue 2, Pages: 167-172(2020)
- 作者机构：
  
  四川轻化工大学自动化与信息工程学院, 四川宜宾 644005
- 作者简介：
- 基金信息：
- DOI：10.3788/YJYXS20203502.0167
  CLC： TP391
- Received：29 July 2019，
  
  Revised：09 October 2019，
  
  Accepted：09 October 2019，
  
  Published：05 February 2020
- 稿件说明：
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Yi-dong MA, Shun-yong ZHOU. Salt and pepper noise filtering algorithm based on connectivity detection[J]. Chinese journal of liquid crystals and displays, 2020, 35(2): 167-172.
DOI：

Yi-dong MA, Shun-yong ZHOU. Salt and pepper noise filtering algorithm based on connectivity detection[J]. Chinese journal of liquid crystals and displays, 2020, 35(2): 167-172. DOI： 10.3788/YJYXS20203502.0167.

摘要

为了在滤除图像椒盐噪声的同时保护图像边缘细节，提出了一种基于连通性检测的图像椒盐噪声滤波算法。由于椒盐噪声点的灰度值与正常像素点的灰度值相比往往存在较大差异，本算法先通过比较像素点灰度值与其邻域像素点灰度值，将差异较大的像素点列为疑似噪声点，然后通过检测疑似噪声点是否是图像连通区域的一部分来判断该点是否是噪声点，最后通过中值滤波器将噪声点滤除。该算法可以有效区分图像区域边缘与椒盐噪声。实验结果表明，该算法可以有效去除密度范围从0~0.9的椒盐噪声，在0.9的噪声密度下，算法的峰值信噪比仍可达到30 dB。满足有效去除不同密度范围的椒盐噪声的同时保护图像细节的要求。

Abstract

In order to protect the image edge details while filtering out the image salt and pepper noise

an image salt and pepper noise filtering algorithm based on connectivity detection is proposed. Since the gray value of the salt and pepper noise point tends to be different from the gray value of the normal pixel point

the algorithm compares the pixel point gray value with the gray value of the neighborhood pixel point to make the pixel point with larger difference. It is listed as a suspected noise point

and then it is judged whether the point is a noise point by detecting whether the suspected noise point is a part of the image connected area. The noise point is finally filtered out by the median filter. The algorithm can effectively distinguish the edge of the image area from the salt and pepper noise. The experimental results show that the algorithm can effectively remove the salt and pepper noise with the density ranging from 0 to 0.9. The peak signal-to-noise ratio of the algorithm can still reach 30 dB with the noise density of 0.9. It satisfies the requirement to effectively remove the salt and pepper noise of different density ranges while protecting the image details.

关键词

Keywords

references

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