K-means method/median filter algorithm and recursive realization

doi:10.3778/j.issn.1002-8331.2009.17.008

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (17): 26-27.DOI: 10.3778/j.issn.1002-8331.2009.17.008

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K-means method/median filter algorithm and recursive realization

HUANG Ying^1,2,WANG Wei-xing²

1.College of Computer Science & Technology，Chongqing University of Posts & Telecommunications，Chongqing 400065，China
2.School of Electronic Engineering，University of Electronic Science & Technology of China，Chengdu 610054，China

Received:2009-03-24 Revised:2009-04-24 Online:2009-06-11 Published:2009-06-11
Contact: HUANG Ying

K均值和中值滤波混合算法及其递归实现

黄颖^1,2,王卫星²

1.重庆邮电大学计算机科学与技术学院，重庆 400065
2.电子科技大学电子工程学院，成都 610054

通讯作者: 黄颖

Abstract

Abstract: This paper designs a K-means median filter algorithm and recursive K-means median filter algorithm to solve the defects of standard median filter.At first，the sample composed by the current pixel and its neighbors is divided into two classes，and the median of the class which includes the current pixel is computed as the result.To ensure the accuracy and speed up the process，two parameters T_L and T_Hare designed.The standard K-means algorithm is a time-consuming procedure，so the optimization is processed in this paper.The experiment proves that the new algorithms can get better noise reduction effect.

Key words: image processing, K-means method, median filter, recursive realization

摘要： 针对标准中值滤波算法边缘保持能力较差的缺点，设计了K均值中值滤波算法和递归K均值中值滤波算法。使用K均值方法将中心像素点的邻域数据序列分成两类，将该像素点所属的这类数据的中值作为输出。为了加快算法的速度，提出了两个阈值T_L和T_H，保证在不影响结果精确性的同时尽量减少处理时间。传统的K均值算法耗时较高，论文的另一个改进是对K均值的优化处理，大大缩短了算法的处理时间。实验证明改进算法具有较好的噪声抑制能力和边缘保持能力。

关键词: 图像处理, K均值方法, 中值滤波, 递归实现

HUANG Ying^1,2,WANG Wei-xing². K-means method/median filter algorithm and recursive realization[J]. Computer Engineering and Applications, 2009, 45(17): 26-27.

黄颖^1,2,王卫星². K均值和中值滤波混合算法及其递归实现[J]. 计算机工程与应用, 2009, 45(17): 26-27.

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K-means method/median filter algorithm and recursive realization

K均值和中值滤波混合算法及其递归实现

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