一种去除椒盐噪声的自适应模糊中值滤波算法
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摘要
针对传统中值滤波算法降噪性能不佳以及易造成图像细节模糊的问题,提出了一种自适应模糊中值滤波算法。滤波过程分为噪声检测和噪声去除2个阶段。噪声检测阶段:采用极值法检测噪声,将图像的像素点分为两类,即疑似噪声点和信号点。通过疑似像素点和与其相邻的已处理的像素点的平均绝对灰度差值定义模糊隶属度函数,利用该函数对疑似噪声点是否为噪声进行模糊分类。噪声去除阶段:信号点保持原值输出,对于疑似噪声点的3种分类结果,采用模糊加权的中值滤波器进行统一处理。实验结果表明,较于多种传统滤波方法,该算法能更有效地去除椒盐噪声,保护图像细节。
An adaptive fuzzy median filtering algorithm is proposed for the problem that traditional median filtering algorithm has poor processing performance in denoising and easily blurs image details. The process of denoising includes two stages: noise detection and noise removal. In noise detection stage, using the maximum-minimum method to detect noise, pixels in a corrupted image are classified into two categories: suspected noise pixels and signal pixels.The fuzzy membership function is defined by the mean of the absolute gray difference between the suspected pixels and its neighborhood pixels which has been processed, and the suspected pixels are fuzzy classified by this function. In noise removal stage, the signal pixels retain unchanged; For the three classification results of suspected noise points, the fuzzy weighted median filter is used for processing. The experimental results show that compared with several traditional filtering algorithm, the proposed algorithm can reduce salt and pepper noise and preserve image details more effectively.
An adaptive fuzzy median filtering algorithm is proposed for the problem that traditional median filtering algorithm has poor processing performance in denoising and easily blurs image details. The process of denoising includes two stages: noise detection and noise removal. In noise detection stage, using the maximum-minimum method to detect noise, pixels in a corrupted image are classified into two categories: suspected noise pixels and signal pixels.The fuzzy membership function is defined by the mean of the absolute gray difference between the suspected pixels and its neighborhood pixels which has been processed, and the suspected pixels are fuzzy classified by this function. In noise removal stage, the signal pixels retain unchanged; For the three classification results of suspected noise points, the fuzzy weighted median filter is used for processing. The experimental results show that compared with several traditional filtering algorithm, the proposed algorithm can reduce salt and pepper noise and preserve image details more effectively.
引文
[1]陈家益,黄楠,熊刚强,等.基于灰度最值和方向纹理的概率滤波算法[J].计算机工程与应用, 2017, 53(8):186-192.CHEN J Y, HUANG N, XIONG G Q, et al.Probability filtering algorithm based on maximum and minimum gray and directional texture[J].Computer Engineering and Application, 2017, 53(8):186-192.
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[10]曾宪佑,黄佐华.一种新型的自适应模糊中值滤波算法[J].计算机工程与应用, 2014, 50(17):134-136,199.ZENG X Y, HUANG Z H. New adaptive fuzzy median filtering algorithm[J].Computer Engineering and Applications, 2014,50(17):134-136,199.
[11]王贵君,杨永强.基于高概率椒盐噪声的模糊滤波器在图像恢复中的算法设计[J].电子学报, 2015, 43(1):24-29.WANG G J, YANG Y Q.Algorithm design of fuzzy filter based on salt-and-pepper noise with high probability in image restoration[J].Acta Electronica Sinica, 2015, 43(1):24-29.
[12] TOH K K V, ISA N A M. Noise adaptive fuzzy switching median filter for salt-and-pepper noise reduction[J].IEEE Signal Processing Letters, 2010,17(3):281-284.
[13]褚江,陈强,杨曦晨.全参考图像质量评价综述[J].计算机应用研究, 2014, 31(1):13-22.CHU J, CHEN Q, YANG X C.Review on full reference image quality assessment algorithms[J].Application Research of Computers, 2014, 31(1):13-22.
[14] FARAGALLAH O S, IBRAHEM H M. Adaptive switching weighted median filter framework for suppressing salt-and-pepper noise[J].AEU-International Journal of Electronics and Communications, 2016, 70(8):1034-1040.
[15] RIJI R, PILLAI K A S, NAIR M S, et al. Fuzzy based directional weighted median filter for impulse noise detection and reduction[J].Fuzzy Information&Engineering, 2012, 4(4):351-369.
[2] NODES T, GALLAGHER N C J. Median filters:Some modifications and their properties[J].IEEE Transactions Acoustics Speech Signal Processing,1982, 30(5):739-746.
[3] HWANG H, HADDAD R A. Adaptive median filters:New algorithms and results[J].IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 1995, 4(4):499-502.
[4]刘颖,陈谨女.自适应中值滤波算法在图像处理中的应用[J].物联网技术, 2013(3):51-52.LIU Y, CHEN J N. Application of adaptive median filtering algorithm in image processing[J].Internet of Things Technologies, 2013(3):51-52.
[5] TANG R, ZHOU X, WANG D. Improved adaptive median filter algorithm for removing impulse noise from grayscale images[J].International Journal of Engineering-Transactions A:Basics, 2017, 30(10):1503-1509.
[6]乔坤,郭朝勇,毛东.一种去除椒盐噪声的自适应开关中值滤波算法[J].计算机应用与软件, 2011, 28(10):253-256.QIAO K, GUO C Y, MAO D. An adaptive switch median filtering algorithm for salt and pepper noise[J].Computer Applications and Software, 2011, 28(10):253-256.
[7]徐少平,杨荣昌,刘小平.基于噪声估计的自适应开关型中值滤波器[J].光电子·激光, 2014(4):792-800.XU S P, YANG R C, LIU X P.Adaptive switching median filter based on noise ratio estimation[J].Journal of Optoelectronics·Laser, 2014(4):792-800.
[8]宗永胜,胡晓辉,张荣光.一种自适应双阈值中值滤波方法[J].小型微型计算机系统, 2017, 38(7):1642-1647.ZONG Y S, HU X H, ZHANG R G.Adaptive dualthreshold median filtering method[J].Journal of Chinese Computer Systems, 2017, 38(7):1642-1647.
[9]王芳,满益云.基于模糊中值滤波的椒盐噪声去除方法[J].模糊系统与数学, 2012, 26(1):166-174.WANG F, MAN Y Y. Salt-and-pepper noise removal based on fuzzy median filtering[J].Fuzzy Systems and Mathematics, 2012, 26(1):166-174.
[10]曾宪佑,黄佐华.一种新型的自适应模糊中值滤波算法[J].计算机工程与应用, 2014, 50(17):134-136,199.ZENG X Y, HUANG Z H. New adaptive fuzzy median filtering algorithm[J].Computer Engineering and Applications, 2014,50(17):134-136,199.
[11]王贵君,杨永强.基于高概率椒盐噪声的模糊滤波器在图像恢复中的算法设计[J].电子学报, 2015, 43(1):24-29.WANG G J, YANG Y Q.Algorithm design of fuzzy filter based on salt-and-pepper noise with high probability in image restoration[J].Acta Electronica Sinica, 2015, 43(1):24-29.
[12] TOH K K V, ISA N A M. Noise adaptive fuzzy switching median filter for salt-and-pepper noise reduction[J].IEEE Signal Processing Letters, 2010,17(3):281-284.
[13]褚江,陈强,杨曦晨.全参考图像质量评价综述[J].计算机应用研究, 2014, 31(1):13-22.CHU J, CHEN Q, YANG X C.Review on full reference image quality assessment algorithms[J].Application Research of Computers, 2014, 31(1):13-22.
[14] FARAGALLAH O S, IBRAHEM H M. Adaptive switching weighted median filter framework for suppressing salt-and-pepper noise[J].AEU-International Journal of Electronics and Communications, 2016, 70(8):1034-1040.
[15] RIJI R, PILLAI K A S, NAIR M S, et al. Fuzzy based directional weighted median filter for impulse noise detection and reduction[J].Fuzzy Information&Engineering, 2012, 4(4):351-369.