Improved Adaptive Median Filtering Algorithm
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    The adaptive median filtering algorithm can effectively filter the impulse noise of image, however, with the noise density increasing, its filtering performance decreases progressively. For the improved median filtering algorithms of current, there are also relevant limitations. Against the limitations of the median filtering algorithm, an improved adaptive median filtering algorithm is proposed. It does noise detection based on the gray extremum of the filtering window. And it replaces the noise point with the gray median of the filtering window. If the gray median is noise point, it increases adaptively the filtering window to take a new gray median. If the filtering window has increased to the maximum size of allowed, and the gray median is still noise point, it takes the gray mean of the pixels except the gray extremum in the filtering window. Simulation experiment has been carried out for standard image and medical image, the results and datum of the filtering experiment demonstrate that, with the noise density increasing, the filtering performance of the standard adaptive median filtering algorithm decreases progressively; and the filtering performance of improved adaptive median filtering algorithm is still good, it maintains well the edges and details of image while filtering effectively the noise.

    Reference
    Related
    Cited by
Get Citation

黄文笔,战荫伟,陈家益,徐秋燕.改进的自适应中值滤波算法.计算机系统应用,2018,27(10):183-188

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:December 22,2017
  • Revised:January 11,2018
  • Adopted:
  • Online: September 29,2018
  • Published:
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063