计算机应用 ›› 2012, Vol. 32 ›› Issue (03): 736-738.DOI: 10.3724/SP.J.1087.2012.00736

• 图形图像技术 • 上一篇    下一篇

基于斜率的自适应中值滤波算法

刘淑娟1,赵晔2,董蕊3,王志巍1,杨芳芳1   

  1. 1.河北师范大学 数学与信息科学学院, 石家庄 050016;
    2.石家庄铁道大学 数理系, 石家庄 050043;
    3.河北交通职业技术学院 基础教学部, 石家庄 050091
  • 收稿日期:2011-08-15 修回日期:2011-11-16 发布日期:2012-03-01 出版日期:2012-03-01
  • 通讯作者: 刘淑娟
  • 作者简介:刘淑娟(1970-),女,河北定州人,讲师,硕士,主要研究方向:图形图像处理;赵晔(1977-),女,河北石家庄人,讲师,博士,主要研究方向:计算几何与图形学; 董蕊(1979-),女,河北石家庄人,讲师,硕士,主要研究方向:图形图像处理;王志巍(1960-),男,辽宁北镇人,副教授,主要研究方向:算法设计、图像处理;杨芳芳(1984-),女,河北廊坊人,硕士研究生,主要研究方向:图形图像处理。
  • 基金资助:

    国家自然科学基金资助项目(10771049)。

Adaptive median filtering algorithm based on slope

LIU Shu-juan1, ZHAO Ye2, DONG Rui3, WANG Zhi-wei1,YANG Fang-fang1   

  1. 1.College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang Hebei 050016, China;
    2.Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang Hebei 050043, China;
    3.Department of Foundamental Teaching, Hebei Jiaotong Vocational and Technical College, Shijiazhuang Hebei 050091, China
  • Received:2011-08-15 Revised:2011-11-16 Online:2012-03-01 Published:2012-03-01
  • Contact: Shu-Juan LIU

摘要: 针对图像中椒盐噪声点的准确检测与去除问题,提出一种基于斜率的自适应中值滤波算法。该算法首先用n×n(n为大于或等于3的奇数)的模板作用于待检测图像的每一个像素,若当前像素的灰度值为其邻域内所有像素灰度值的极值,判断此点为准噪声点;再利用像素灰度值序列中两段子序列斜率的差值及模板区域内像素灰度值的均值自适应地判断准噪声点是否为真正的噪声点;最后对被判定为噪声的像素做中值滤波处理。与标准中值滤波方法相比,该方法加强了噪声检测的条件。实验结果表明,该算法具有较好地去除椒盐噪声和保留细节的效果。

关键词: 噪声检测, 椒盐噪声, 斜率差值, 中值滤波, 图像去噪

Abstract: For estimating and removing the salt-and-pepper noise point accurately in image, a new adaptive median filtering algorithm was proposed.Firstly, if the pixel in the center of n×n (n is an odd integer not less than three) template was the extreme value of all the pixels in the window, it was supposed to be probably a noise point. The pixel gray value in the sequence difference between the two scripts and a template sequence of the slope of the pixel gray value within the region were used to determine the mean quasi-adaptive noise point to be the real noise points. Finally, mean filtering was done on the noised pixels. Compared with median filter, the condition of detecting noises with this method has been largely enhanced. And the method can both effectively restrain noises and maintain details.

Key words: noise detection, salt-and-pepper noise, slope difference value, median filtering, image denoising

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