Computer Science ›› 2017, Vol. 44 ›› Issue (8): 301-305.doi: 10.11896/j.issn.1002-137X.2017.08.052

Previous Articles     Next Articles

Algorithm of Image Salt and Pepper Noise Elimination Based on Particle Swarm Algorithm

ZHANG Ai-ling, LI Peng and LIU Sheng   

  • Online:2018-11-13 Published:2018-11-13

Abstract: To eliminate salt and pepper noise in images,we proposed an adaptive switching median filter algorithm based on particle swarm algorithm. The proposed algorithm consists of two stages:noise detection and noise filtering.Compared with the standard median filtering,the adaptive switching median filter algorithm was put forward to generate pollution image noise wave. Contaminated and non-contaminated pixel information can be get through the noise wave images.In the filtering process,the filter calculates the value of the adjacent pixels and replaces the contaminated pixels.The simulation results show that the proposed algorithm is effective and can improve the peak signal to noise ratio (SNR) and image quality.

Key words: Median filter,Particle swarm algorithm,Noise elimination,Impulse noise,Image denoising,PSNR,NMSE

[1] RAHIMI S,AGHAGOLZADEH A,SEY EDARABI H.Human detection and tracking using new features combination in particle filter framework[J].Machine Vision & Image Processing,2014,2(7):349-354.
[2] PENG Y,WU T,WANG S,et al.Motion-blurred particle image restoration for on-line wear monitoring[J].Sensors,2015,15(4):8173-8191.
[3] GAO Z Q,ZHUANG J J.Research on image denoising method based on parameter self adjusting switching median filter [J].Journal of Laser,2015,36(10):50-54.(in Chinese) 高振清,庄建军.基于参数自调整开关中值滤波的图像去噪方法研究[J].激光杂志,2015,36(10):50-54.
[4] ZHAO M,GONG S R,GAO Z J.Mixed noise filtering algorithm based on gray correlation coefficient [J].Computer Engineering and Design,2014,35(5):1713-1716.(in Chinese) 赵敏,龚声蓉,高祝静.基于灰色关联系数的混合噪声滤波算法[J].计算机工程与设计,2014,35(5):1713-1716.
[5] TANG X H,ZHENG Y,YANG Q W.Mesh filtering algorithm for mixed noise based on [J].Microelectronics and Computer,2016,33(6):87-91.(in Chinese) 唐向红,郑阳,杨全纬.基于网格划分的混合噪声滤波算法[J].微电子学与计算机,2016,33(6):87-91.
[6] VIJAYKUMAR V R,SANTHANAMARI G,ELANGO S.VLSI Architecture of Switching Median Filter for Salt and Pepper Noise Removal[J].Iaeng International Journal of Computer Science,2016,43(1):44-54.
[7] DESHPANDE B,VERMA H K,DESHPANDE P.Fuzzy Based Median Filtering for Removal of Salt-and-Pepper Noise[J].International Journal of Soft Computing & Engineering,2012,2(3):76-80.
[8] LU C T,CHOU T C.Denoising of salt-and-pepper noise corrupted image using modified directional-weighted-median filter[J].Pattern Recognition Letters,2012,33(10):1287-1295.
[9] FARAGALLAH O S,IBRAHEM H M.Adaptive switching wei-ghted median filter framework for suppressing salt-and-pepper noise[J].AEU-International Journal of Electronics and Communications,2016,70(8):1034-1040.
[10] LIU S X,WANG X C,CHANG C W.Otsu image segmentation method based on Improved Particle Swarm Optimization [J].Computer Science,2013,40(8):293-295.(in Chinese) 刘申晓,王学春,常朝稳.基于改进粒子群优化算法的Otsu图像分割方法[J].计算机科学,2013,40(8):293-295.
[11] WANG H T,LI D.Research on image enhancement based on Im-proved Particle Swarm Optimization[J].Journal of Graphi-cs,2013,34(6):87-92.(in Chinese) 王洪涛,李丹.基于改进粒子群算法的图像灰度增强研究[J].图学学报,2013,34(6):87-92.
[12] NAIR M S,SHANKAR V.Predictive-based adaptive switching median filter for impulse noise removal using neural network-based noise detector[J].Signal,Image and Video Processing,2013,7(6):1041-1070.
[13] EBERHART R C,SHI Y.Particle swarm optimization:develo-pments,applications and resources[C]∥Proceedings of the 2001 Congress on Evolutionary Computation.IEEE,2001,1(6):81-86.
[14] CHEN P,ZOU T,CHEN J Y,et al.The Application of Im-proved PSO Algorithm in PMMW Image OSTU Threshold Segmentation[J].Applied Mechanics & Materials,2014,721:779-782.
[15] SULAIMAN S N,ISA N A M.Denoising-based clustering algorithms for segmentation of low level salt-and-pepper noise-corrupted images[J].Signal,Image and Video Processing,2015,9(2):387-398.
[16] LI W G,ZHAO X M.Multi-wavelet image denoising based on artificial bee colong algorithm[J].Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition),2013,5(4):532-537.(in Chinese) 李万高,赵雪梅.基于蜂群算法的多小波图像去噪研究[J].重庆邮电大学学报(自然科学版),2013,5(4):532-537.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .