计算机科学 ›› 2018, Vol. 45 ›› Issue (10): 250-254.doi: 10.11896/j.issn.1002-137X.2018.10.046

• 图形图像与模式识别 • 上一篇    下一篇

基于二级修复的多方向加权均值滤波算法

马洪晋, 聂玉峰   

  1. 西北工业大学理学院 西安710072
  • 收稿日期:2018-03-26 出版日期:2018-11-05 发布日期:2018-11-05
  • 作者简介:马洪晋(1990-),女,博士生,主要研究方向为图像处理和科学计算等;聂玉峰(1968-),男,博士,教授,主要研究方向为科学计算和并行算法等,E-mail:yfnie@nwpu.edu.cn(通信作者)。
  • 基金资助:
    国家自然科学基金(11471262)资助

Multi-directional Weighted Mean Denoising Algorithm Based on Two Stage Noise Restoration

MA Hong-jin, NIE Yu-feng   

  1. School of Natural and Applied Sciences,Northwestern Polytechnical University,Xi’an 710072,China
  • Received:2018-03-26 Online:2018-11-05 Published:2018-11-05

摘要: 针对目前算法不能有效去除高概率的椒盐噪声并保护图像边缘和细节特征的缺点,提出了一种基于二级修复的多方向加权均值滤波算法。在噪声检测阶段,首先利用一个方差参数判断当前像素点与其邻域像素点之间的灰度差异程度,再通过将方差参数和灰度极值相结合的方法检测出图像中的椒盐噪声点。在噪声修复阶段,提出一种二级修复方法来修复噪声点的灰度值。首先利用改进的自适应中值滤波器对椒盐噪声点进行第一级噪声修复;然后利用方差参数将第一级修复后的噪声点划分为两类,并采用不同的修复方法对这两类像素点进行第二级噪声修复,一类像素点采用均值滤波器进行再修复,另外一类像素点采用多方向加权均值滤波器进行再修复。数值实验结果表明,所提算法的滤波性能和边缘保护能力均优于当下很多先进的滤波器。

关键词: 多方向加权均值滤波, 二级修复方法, 方差参数, 椒盐噪声, 图像去噪

Abstract: In view of problem that some present algorithms cannot effectively remove salt-and-pepper noise meanwhile preserving edges and details in the case of high noise density,a multi-directional weighted mean denoising algorithm based on two stage noise restoration was proposed.In the noise detection stage,the proposed algorithm firstly introduces a variance parameter to judge the gray level difference between current pixel and its neighborhood pixels,then designs the noise detector by combining the variance parameter and gray level extreme.In the noise restoration stage,a two stage restoration method is introduced to restore the gray value of noisy pixels.Firstly,the restoration method uses the improved adaptive median filter to carry out the first stage noise restoration,then divides all the noisy pixels into two types and applies different restoration skills to carry out the second stage noise restoration.One type of noisy pixel is further restored by the mean filter and the other type of noisy pixel is further restored by the multi-directional weighted mean filter.Experimental results show that the proposed algorithm outperforms many state-of-the-art filters in terms of image denoising and edge preservation.

Key words: Image denoising, Multi-directional weighted mean filter, Salt-and-pepper noise, Two stage restoration method, Variance parameter

中图分类号: 

  • TN911
[1]TANG H S,NI R R,ZHAO Y,et al.Median filtering detection of small-size image based on CNN [J].Journal of Visual Communication and Image Representation,2018,51:162-168.
[2]ZHANG A L,LI P,LIU S.Algorithm of image salt and pepper noise elimination based on particle swarm algorithm [J].Computer Science,2017,44(8):301-305.(in Chinese)
张爱玲,李鹏,刘晟.基于粒子群算法的图像椒盐噪声去除算法[J].计算机科学,2017,44(8):301-305.
[3]JIAO Y,WU J S,JIAO L C.An image segmentation method based on network clustering model [J].Physica A:Statistical Mechanics and Its Applications,2018,490:1532-1542.
[4]WANG J Q,BI J,WANG L J,et al.A non-reference evaluation method for edge detection of wear particles in ferrograph images [J].Mechanical Systems and Signal Processing,2018,100:863-876.
[5]CHENG J,ZHU J M,WU J.Double level set image segmentation based on image layer [J].Computer Science,2015,42(6):308-312.(in Chinese)
陈静,朱家明,吴杰.基于图像层的双水平集图像分割 [J].计算机科学,2015,42(6):308-312.
[6]HUANG T,YANG G,TANG G.A fast two-dimensional median filtering algorithm [J].IEEE Transactions on Acoustics,Speech,and Signal Processing,1979,27(1):13-18.
[7]HWANG H,HADDAD R.Adaptive median filters:new algorithms and results [J].IEEE Transactions on Image Proces-sing,1995,4(4):499-502.
[8]HUANG Y,LEI T,FAN Y Y,et al.Adaptive decision-based unsymmetric trimmed median filter [J].Computer Science,2015,42(1):303-307.(in Chinese)
黄燕,雷涛,樊养余,等.基于自适应窗口的裁剪中值滤波方法[J].计算机科学,2015,42(1):303-307.[9]BROWNRIGG D.The weighted median filter [J].Image Processing and Computer Vision,1984,27(8):807-818.
[10]ROY A,SINGHA J,MANAM L,et al.Combination of adaptive vector median filter and weighted mean filter for removal of high-density impulse noise from colour images [J].IET Image Processing,2017,11(6):352-361.
[11]ZHANG Z,HAN D Q,DEZERT J,et al.A new adaptive switching median filter for impulse noise reduction with pre-detection based on evidential reasoning [J].Signal Processing,2018,147:173-189.
[12]ZENG X Y,HUANG Z H,ZHOU J Z.Switching median filter with boundary discriminative noise detection [J].Computer Engineering and Applications,2014,50(14):176-179.(in Chinese)
曾宪佑,黄佐华,周进朝.基于差分分层噪声检测的开关中值滤波算法 [J].计算机工程与应用,2014,50(14):176-179.
[13]ZHANG S,KARIM M.A new impulse detector for switching median filters [J].IEEE Signal Processing Letters,2002,9(11):360-363.
[14]NG P,MA K.A switching median filter with boundary discriminative noise detection for extremely corrupted images [J].IEEE Transactions on Image Processing,2006,15(6):1506-1516.
[15]DONG Y Q,XU S F.A new directional weighted median filter for removal of random-valued impulse noise [J].IEEE Signal Processing Letters,2007,14(3):193-196.
[16]LU C T,CHOU T C.Denoising of salt-and-pepper noise corrupted image using modified directional weighted median filter [J].Pattern Recognition Letters,2012,3(10):1287-1295.
[17]LI Z Y,LIU G H,XU Y,et al.Modified directional weighted filter for removal of salt & pepper noise [J].Pattern Recognition Letters,2014,40(15):113-120.
[18]LU C T,CHEN Y Y,WANG L L,et al.Removal of salt-and-pepper noise in corrupted image using three-values-weighted approach with variable-size window [J].Pattern Recognition Letters,2016,80(C):188-199.
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