一种基于开关型加权中值滤波的随机脉冲噪声去除方法

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英文篇名：A Random-value Impulse Noise Removal Method Based on Switching Weighted Median Filter 作者：史再峰 ; 许泽昊 ; 庞科 ; 曹清洁 ; 姚素英 英文作者：Shi Zaifeng;Xu Zehao;Pang Ke;Cao Qingjie;Yao Suying;School of Microelectronics, Tianjin University;School of Computer Science and Technology, Tianjin University;School of Mathematical Sciences, Tianjin Normal University; 关键词：随机脉冲噪声 ; 中值滤波 ; 噪声检测 ; 噪声滤除 英文关键词：impulse noise;;median filter;;noise reduction;;detection accuracy 中文刊名：NKDZ 英文刊名：Acta Scientiarum Naturalium Universitatis Nankaiensis 机构：天津大学微电子学院;天津大学计算机科学与技术学院;天津师范大学数学科学学院; 出版日期：2018-08-20 出版单位：南开大学学报(自然科学版) 年：2018 期：v.51 基金：国家高技术研究发展计划(2012AA012705);; 国家自然科学基金(61674115) 语种：中文; 页：NKDZ201804011 页数：5 CN：04 ISSN：12-1105/N 分类号：65-69

摘要

依据图像中随机脉冲噪声像素奇异性的特点,提出了1种新的开关型加权中值滤波算法.首先通过中值滤波的方法对被检测像素邻域进行平滑处理,并定义平均绝对差值进行噪声点的判别;对检测出的噪声像素点采用改进的加权中值滤波进行处理,即仅利用滤波窗口中未受污染的像素进行噪声滤除,加权系数同时包括空间距离与灰度的差异性.实验结果表明,提出的算法既有较高的脉冲噪声检测准确率,又能较好地滤除图像中的随机脉冲噪声.
        According to the singular characteristics of impulse noise, a new switching median filter was put forward to remove random-value impulse noise. The median filter was first applied for smoothing noise around the central pixel and the mean absolute difference was defined to distinguish whether the detected pixel was noisy. Then an improved weighted median filter which only chose unpolluted pixels was proposed for noise reduction. The spatial distance and gray-value difference were both taken into account when calculating weighted coefficient. The experiment results show that the proposed algorithm not only produces higher detection accuracy but also exhibits better noise removal capability.

引文

1 Xu Jiangtao,Wang Lei,Shi Zaifeng.A switching weighted vector median filter based on edge detection[J].Signal Processing,2014,98:359-369.
    2 Liu Licheng,Chen Long,Philip Chen C L,et al.Weighted joint sparse representation for removing mixed noise in image[J].IEEE Transactions on Cybernetics,2017,47(3):600-611.
    3 杨幸芳,张梦文,严凯,等.一种改进的脉冲噪声的检测与滤除算法[J].西安工程大学学报,2014,28(4):480-484.
    4 金良海,李德华.基于噪声检测的图像去噪算法[J].模式识别与人工智能,2008,21(3):298-302.
    5 Ko S J,Yong H L.Center weighted median filters and their applications to image enhancement[J].IEEE Transactions on Circuits and Systems,1991,38(9):984-993.
    6 Alajlan N,Kamel M,Jernigan E.Detail preserving impulsive noise removal[J].Signal Processing:Image Communication,2004,19(10):993-1 003.
    7 李迅波,蒋东升,王振林.梯度相似性的椒盐图像加权中值滤波算法[J].电子科技大学学报,2012,41(1):114-119.
    8 Chen Tao,Wu Hongren.Adaptive impulse detection using center-weighted median filters[J].IEEE Signal Processing Letters,2001,8(1):1-3.
    9 Crnojevic?V,Senk V,Trpovski Z.Advanced impulse detection based on pixel-wise MAD[J].IEEE Signal Processing Letters,2004,11(7):589-592.
    10 Akkoul S,Ledee R,Leconge R,et al.A new adaptive switching median filter[J].IEEE Signal Processing Letters,2010,17(6):587-590.
    11 Xiong Bo,Yin Zhouping.A universal denoising framework with a new impulse detector and nonlocal means[J].IEEE Transactions on Image Processing,2012,21(4):1 663-1 675.
    12 黄琪,李鼎权,施涛,等.一种针对椒盐噪声的新型迭代自适应滤波器[J].南开大学学报:自然科学版,2015,48(5):84-89.
    13 Jiang J,Zhang L,Yang J.Mixed noise removal by weighted encoding with sparse nonlocal regularization[J].IEEE Transactions on Image Processing,2014,23(6):2 651-2 662.