[1]陈庆强,蔡文培,邹复民.高效快速的随机值脉冲噪声去除算法[J].福建工程学院学报,2018,16(03):242-247.[doi:10.3969/j.issn.1672-4348.2018.03.008]
　CHEN Qingqiang,CAI Wenpei,ZOU Fumin.Algorithm of the effective and quick removal of random impulse noises[J].Journal of FuJian University of Technology,2018,16(03):242-247.[doi:10.3969/j.issn.1672-4348.2018.03.008]
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高效快速的随机值脉冲噪声去除算法()
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《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第16卷
期数:
2018年03期
页码:
242-247
栏目:
出版日期:
2018-06-25

文章信息/Info

Title:
Algorithm of the effective and quick removal of random impulse noises
作者:
陈庆强; 蔡文培; 邹复民
福建工程学院信息科学与工程学院
Author(s):
CHEN Qingqiang;  CAI Wenpei;  ZOU Fumin
School of Information Science and Engineering, Fujian University of Technology
关键词:
随机值脉冲噪声;  噪声检测;  欧拉距离;  图像滤波;  自适应
Keywords:
random impulse noise;  noise pixel detection;  Euler distance;  image filtering;  self-adaption
分类号:
TP391
DOI:
10.3969/j.issn.1672-4348.2018.03.008
文献标志码:
A
摘要:
提出一种既能快速去除图像随机脉冲噪声又能较好地保留边缘细节信息的一种新方法。该方法首先利用图像局部灰度相似性特征，对于任一像素，根据其与邻域内像素相近的个数和与其相近像素本身在邻域内的相似情况，将各像素分为噪声点、疑似噪声点和信号点，对疑似噪声点根据其是否为邻域内的极值将其分为噪声点和信号点。对于信号点不做任何处理，而对于噪声点则按照一种基于欧拉距离的自适应加权均值滤波算法进行处理。实验结果表明，算法能够快速高效地滤除随机脉冲噪声，且无需人为修改相关参数和“门坎”值，综合性能优良，特别适用于对实时性要求较高的图像处理系统。
Abstract:
A new algorithm was put forward that can remove random impulse noises quickly and retain edge details well. The method first utilized the local gray-scale similarity of the image. According to the number of pixels in the neighbourhood of a certain pixel and its similarity with its neighbouring ones, the pixels could be classified into noise pixels, suspected noise pixels and signal pixels. The suspected noise pixels were then divided into poise pixels and signal pixels according to whether they were the extremum in the neighborhood. Signal pixels would not be processed, while noise pixels were processed with an adaptive weight-mean filtering algorithm based on Euler distance. Experimental results indicate that the proposed algorithm can filter out random impulse noises quickly and effectively. Moreover, it does not need manual adjustment of the parameters and thresholds. The proposed method achieves good comprehensive performances, and it is particularly suitable for image processing systems with high real-time requirements.

参考文献/References:

[1] WANG Z, ZHANG D. Progressive switching median filter for the removal of impulse noise from highly corrupted images［J］.IEEE Transactions on Circuits and Systems Ⅱ,1999, 46(1):78-80.
[2] CHEN Q Q, CHANG C Y. A robust noise removal algorithm with consideration of contextual information[J].Multidimensional Systems and Signal Processing,2016,27(1):179-200.
[3] TUKEY J W. Nonlinear (nonsuperposable) methods for smoothing data[C]. Proceedings of Electronics and Aerospace Systems Conference. Washington:[s.n.],1974:673-681.
[4] KO S J, LEE S J. Center weighted median filters and their applications to image enhancement[J]. IEEE Transactions on Circuits and Systems,1991,38(9):984-993.
[5] 金良海,熊才权,李德华.自适应型中心加权的中值滤波器[J].华中科技大学学报(自然科学版),2008,36(8): 9-12.
[6] SUN T, NEUVO Y. Detail-preserving median based filters in image processing[J]. Pattern Recognition Etters,1994，15(4): 341-347.
[7] WANG Z, ZHANG D. Progressive switching median filter for the removal of impulse noise from highly corrupted images［J］. IEEE Transactions on Circuits and Systems Ⅱ,1999,46(1):78-80.
[8] CHEN T, MA K K, CHEN L H. Tri-state median filter for image denoising[J]. IEEE Transactions on Image Processing,1999, 8(12): 1834-1838.
[9] CHAN R H, HU C, NIKOLOVA M. An iterative procedure for removing random-valued impulse noise[J]. IEEE Signal Processing Letters,2005,11(12):921-924.
[10] GARNETT R, HUEGERICH T, CHUI C. A universal noise removal algorithm with an impulse detector [J]. IEEE Transactions on Image Processing,2005,14(11):1747-1754.
[11] DONG Y, CHAN R H, XU S. A detection statistic for random-valued impulse noise [J]. IEEE Transactions on Image Processing, 2007,16(4):1112-1120.
[12] AWAD A S, MAN H, KHASHANAH K. Cascade window-based procedure for impulse noise removal in heavily corrupted images[J]. Journal of Electronic Imaging, 2010,19(1): 013006-10.
[13] 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.
[14] 单建华.种子像素滤波法去除随机脉冲噪声[J].中国图象图形学报,2012,17(1):49-53.
[15] 陈明轩,周亚丽,张奇志.基于12个方向的方向加权滤波法去除随机值脉冲噪声[J].计算机应用研究,2014,31(5):1584-1587.
[16] 周艳,唐权华,蒋朝哲.图像快速自适应加权中值滤波[J].微计算机信息,2008,24(7):168-169,155.
[17] 曹振华.嵌入式实时系统图像滤波算法研究[J].苏州大学学报（工科版）,2010,30(1):37-41.
[18] 杨晶,王元庆.实时高速实现改进型中值滤波算法[J].计算机与现代化,2013(8):30-32.
[19] 佟雨兵,张其善,祁云平.基于PSNR与SSIM联合的图像质量评价模型[J].中国图象图形学报,2006,11(12):1758-1763.

更新日期/Last Update: 2018-06-25