|Table of Contents|

Adaptive weighted mean filtering algorithm based onconfidence interval(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2017年03期
Page:
307-
Research Field:
Publishing date:

Info

Title:
Adaptive weighted mean filtering algorithm based onconfidence interval
Author(s):
Chen Jiayi1Huang Nan2Xiong Gangqiang1Cao Huiying1Xu Qiuyan3
1.School of Information Engineering,Guangdong Medical University,Zhanjiang 524023,China; 2.School of Science,Nanjing University of Science and Technology,Nanjing 210094,China; 3.Surgical Intensive Care Unit,Center People’s Hospital of Zhanjiang,Zhanjiang 524037,China
Keywords:
confidence interval mean filtering algorithm adaptive filtering algorithm Gaussian noise gray correlation distance correlation
PACS:
TP391
DOI:
10.14177/j.cnki.32-1397n.2017.41.03.006
Abstract:
An adaptive weighted mean filtering algorithm based on a confidence interval is proposed to improve the results of filtered images.The weighted means of the pixels in a filtering window and within the confidence interval are calculated according to the characteristics of Gaussian noise and its effect on an original image.A weighted coefficient is obtained by the linear weighted sum of the gray measure factor and distance measure factor,and the gray correlation and distance correlation are taken into consideration.Finally,the gray of the weighted mean filtered image is equalized.The experimental results show that this algorithm is better than the standard mean filtering(SMF)algorithm and adaptive mean filtering(AMF)algorithm,the filtered image is clearer,the original image is recovered well,and the edges and details are kept; the normalized mean square error(NMSE)of this algorithm is lower than that of the SMF and AMF.

References:

[1] Kang Jiayin,Min Lequan,Luan Qingxian,et al.Novel modified fuzzy c-means algorithm with application[J].Digital Signal Processing,2009,19(2):309-319.
[2]Tang Wang,Tang Jin.An improved mean filter algorithm for impulse noise elimination[J].Advanced Material Research,2014,936:2281-2285.
[3]武英,吴海勇.一种自适应图像去噪混合滤波方法[J].计算机工程与应用,2010,46(7):168-170.
Wu Ying,Wu Haiyong.An adaptive mixed filtering algorithm for image denoising[J].Computer Engineering and Application,2010,46(7):168-170.
[4]杨吉宏,胡顺波,张民,等.灰度图像加权有向平滑滤波算法[J].计算机工程与设计,2010,31(1):163-156.
Yang Jihong,Hu Shunbo,Zhang Min,et al.Weighted directional smoothing filtering algorithm for gray image[J].Computer Engineering and Design,2010,31(1):163-156.
[5]Gonzalez R C,Woods R E.Digital image processing[M].Beijing,China:Publishing House of Electronics Industry,2010.
[6]Sakthivel N,Prabhu L.Mean-median filtering for impulsive noise removal[J].International Journal of Basic and Applied Science,2014,2(4):47-57.
[7]Zhang Peixuan,Li Fang.A new adaptive weighted mean filter for removing salt-and-pepper noise[J].IEEE Signal Processing Letters,2014,21(10):1280-1283.
[8]关新平,赵立兴,唐英干.图像去噪混合滤波方法[J].中国图象图形学报,2005,10(3):332-337.
Guan Xinping,Zhao Lixing,Tang Yinggan.Mixed filtering algorithm for image denoising[J].China Journal of Image and Graphics,2005,10(3):332-337.
[9]Fang Jia,Xu Decheng,Fu Xin.An improved hybrid median-mean filter algorithm[J].Applied Mechanics and Materials,2015,701-702:288-292.
[10]Lan Xia,Shen Huanfeng,Zhang Liangpei.An adaptive non-local means filter based on region homogeneity[C]//2013 Seventh International Conference on Image and Graphics.Qingdao,China:ICIG,2013:50-54.
[11]Miao Zhenwei,Jiang Xudong.Weighted iterative truncated mean filter[J].IEEE Transactions on Signal Processing,2013,61(16):4149-4160.
[12]张文娟,康家银.一种用于图像降噪的自适应均值滤波算法[J].小型微型计算机系统,2011,32(12):2495-2498.
Zhang Wenjuan,Kang Jiayin.An adaptive mean filtering algorithm for image denoising[J].Journal of Chinese Computer Systems,2011,32(12):2495-2498.
[13]Zhang Shufang,Zhang Tao,Qu Guangcai,et al.A new adaptive weighted median filter algorithm[J].Energy Procedia,2011,13(5):2987-2993.
[14]陈志敏,薄煜明,吴盘龙,等.收敛粒子群全区域自适应粒子滤波算法及其应用[J].南京理工大学学报,2012,36(5):861-686.
Chen Zhimin,Bo Yuming,Wu Panlong,et al.Adaptive particle filtering algorithm and its application of convergence particle swarm region[J].Journal of Nanjing University of Science and Technology,2012,36(5):861-686.
[15]Singh C,Chauhan R P S,Singh D.Comparative study of image enhancement using median and high pass filtering methods[J].Journal of Information and Operations Management,2012,3(1):96-98.
[16]盛骤,谢式千,潘承毅.概率论与数理统计[M].北京:高等教育出版社,2013:46-50.

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Last Update: 2017-06-30