CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

A Modified Non Linear Median Filter for the Removal of Medium Density Random Valued Impulse Noise

by Govind Ballabh Khan, Sandeep Pratap Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 147 - Number 8
Year of Publication: 2016
Authors: Govind Ballabh Khan, Sandeep Pratap Singh
10.5120/ijca2016911081

Govind Ballabh Khan, Sandeep Pratap Singh . A Modified Non Linear Median Filter for the Removal of Medium Density Random Valued Impulse Noise. International Journal of Computer Applications. 147, 8 ( Aug 2016), 17-22. DOI=10.5120/ijca2016911081

@article{ 10.5120/ijca2016911081,
author = { Govind Ballabh Khan, Sandeep Pratap Singh },
title = { A Modified Non Linear Median Filter for the Removal of Medium Density Random Valued Impulse Noise },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 147 },
number = { 8 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume147/number8/25673-2016911081/ },
doi = { 10.5120/ijca2016911081 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:51:21.096963+05:30
%A Govind Ballabh Khan
%A Sandeep Pratap Singh
%T A Modified Non Linear Median Filter for the Removal of Medium Density Random Valued Impulse Noise
%J International Journal of Computer Applications
%@ 0975-8887
%V 147
%N 8
%P 17-22
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the field of image processing, elimination of noise from digital images plays a vital role. Effective detection of noisy pixel based on median value and an efficient algorithm for the estimation and replacement of noisy pixel has been carried out in this proposed method in which replacement of noisy pixel is carried out twice, which results in better preservation of image details. The presence of high performing detection stage for the detection noisy pixel makes the proposed method suitable in the case of high density random valued impulse noise, hence the proposed method yields better image quality with improved peak signal to noise ratio (PSNR) and reduced mean square error (MSE). Results of proposed method has been compared with many other standard median based switching filters in terms of visual and quantitative measures and the performance of the proposed method is presented.

References
  1. E. Abreu and S. Mitra, “A signal-dependent rank ordered mean (SDROM) filter-a new approach for removal of impulses from highly corrupted images,” in ICASSP, vol. 4, pp. 2371 –2374, 1995 IEEE.
  2. Z. Wang and D. Zhang, “Progressive switching median filter for the removal of impulse noise from highly corrupted images,” IEEE Trans. on Circuits and Systems II: Analog and Digital Signal Processing, vol. 46, no. 1, pp. 78–80, 1999.
  3. R. C. Hardie and K. E. Barner, “ Rank-conditioned rank selection filters for signal restoration ,” IEEE Transactions on Image Processing, vol. 2 pp. 192–206, 1994
  4. Y. Dong and S. Xu, “A new directional weighted median filter for removal of random-valued impulse noise,” IEEE Signal Processing Letters, vol. 14, no.3, pp. 193-196, 2007.
  5. Guoping Qiu, “ An improved Recursive Median Filtering Scheme for Image Processing”, IEEE Trans. on Image Processing, Vol.5, No.4, pp. 646-648. l 1996.
  6. T. Chen, K.-K. Ma, and L.-H. Chen, “Tri-state median filter for image denoising,” IEEE Trans. Image Processing, vol. 8, no. 12, pp. 1834–1838, 1999.
  7. Xiaoyin Xu, Eric L. Miller, Dongbin Chen and Mansoor Sarhadi "Adaptive two-pass rank order filter to remove impulse noise in highly corrupted images", IEEE Transactions on Image Processing, Vol. 13, No. 2, February 2004.
  8. T. Song, M. Gabbouj, and Y. Neuvo, "Center weighted median filters: some properties and applications in image processing," Signal Processing, vol. 35, no. 3, pp. 213-229, 1994.
  9. S.-J. Ko and Y. Lee, “Center weighted median filters and their applications to image enhancement,” IEEE Transactions on Circuits and Systems, vol. 38, no. 9, pp. 984–993, September 1991.
  10. J. Bhabesh Deka and Dipranjan Baishnab “A Linear Prediction Based Switching Median Filter for the Removal of Salt and Pepper Noise from Highly Corrupted Image” in CISP2012 ©2012 IEEE.
  11. Shanmugavadivu P & Eliahim Jeevaraj P S, “Laplace Equation based Adaptive Median Filter for Highly”CorruptedImages”,International Conference on Computer Communication and Informatics (ICCCI -2012), 2012.
  12. Dagao Duan, Yueliang Wan, “A Detail Preserving Filter for Impulse Noise Removal” in International Conference on Computer Application and System Modeling (ICCASM 2010).
  13. Gonzalez R.C, Woods. R.E., Digital Image Processing, 3rd edition, Pearson Prentice Hall, 2009.
  14. Aparna Sarkar, Suvamoy Changder,and J.K.Mandal“A Threshold based Directional Weighted MedianFilter for Removal of Random Impulses in Thermal Images” IEEE-2014(ICBIM)
  15. T. Chen and H.Wu Adaptive impulse detection using centre-weighted median filters, Signal Processing Letter., vol.8, no. 1, pp. 13, Jan. 2001
Index Terms

Computer Science
Information Sciences

Keywords

Mean square error Peak signal to noise ratio Random valued impulse noise switching median filter.

Powered by PhDFocusTM