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Reseach Article

Removal of Impulse Noise using Iterative Unsymmetrical Trimmed Median Filter

by Glincy Mary Jacob, Tony Sam Thomas, Rahna K.m
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 89 - Number 12
Year of Publication: 2014
Authors: Glincy Mary Jacob, Tony Sam Thomas, Rahna K.m
10.5120/15686-4556

Glincy Mary Jacob, Tony Sam Thomas, Rahna K.m . Removal of Impulse Noise using Iterative Unsymmetrical Trimmed Median Filter. International Journal of Computer Applications. 89, 12 ( March 2014), 43-48. DOI=10.5120/15686-4556

@article{ 10.5120/15686-4556,
author = { Glincy Mary Jacob, Tony Sam Thomas, Rahna K.m },
title = { Removal of Impulse Noise using Iterative Unsymmetrical Trimmed Median Filter },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 89 },
number = { 12 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume89/number12/15686-4556/ },
doi = { 10.5120/15686-4556 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:09:05.723258+05:30
%A Glincy Mary Jacob
%A Tony Sam Thomas
%A Rahna K.m
%T Removal of Impulse Noise using Iterative Unsymmetrical Trimmed Median Filter
%J International Journal of Computer Applications
%@ 0975-8887
%V 89
%N 12
%P 43-48
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

It is universally accepted that Median filter is the best filter known so far. Based on this fact many variants of median filter were developed to improve the performance of the standard median filter. In this paper a new approach for the restoration of gray scale and color images that are highly corrupted by impulse noise is proposed. The algorithm works on low density noise also. The algorithm has three stages – firstly, finding the corrupted pixels, secondly de-noising the corrupted pixels; thirdly, minimizing the de-noised image to root image. The article proves that the new approach is guaranteed to converge to root image within a finite number of iterations. The proposed algorithm shows better results than the Standard Median Filter, Recursive Median Filter and Decision based Unsymmetrical Trimmed Median Filter.

References
  1. R. C. Gonzalez, and Woods R. E, "Digital Image Processing". Addison-Wesley, Boston, 2005.
  2. W. K. Pratt, "Median filtering", Image Processing, Institute, University of Southern California, Los Angeles, Technical Report, 1975.
  3. G. Qiu, "Functional optimization properties of median filtering", IEEE Signal Processing Letter. , vol. 1, no. 4, pp. 64-65, 1994.
  4. H. Hwang and R. A. Hadded, "Adaptive median filter: New algorithms and results," IEEE Transactions on Image Processing, vol. 4, pp499-502.
  5. S. Esakkirajan, T. Veerakumar, Adabala N. Subramanyam and C. H. PremChand, "Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter", IEEE Signal Processing Letters, Vol. 18, NO. 5, May 2011.
  6. K. Aiswarya,V. Jayaraj,and D. Ebenezer, "A new and efficient algorithm for the removal of high density salt and pepper noise in image and video," in second International Conference on Computer Modeling and Simulation, 2010, pp. 409-413.
  7. K. S. Srinivasan and D. Ebenezer, "A new fast and efficient decision based algorithm for removal of high density impulse noise," IEEE signal processing, Letter, vol. 14, no. 3, pp. 189-192, Mar. 2007.
  8. G. R. Arce and M. P. McLoughlin, "Theoretical analysis of max/median filters," IEEE Transaction. Acoustic, Speech, Signal Processing, vol. ASSP-35, pp. 60-69, 1987.
  9. G. R. Arce and R. E. Foster, "Detail-preserving ranked-order based filters for image processing," IEEE Trans. Acoustic, Speech, Signal Processing, vol. ASSP-37, pp. 83-98, 1989.
  10. Guoping Qiu "An Improved Recursive Median Filtering Scheme for Image Processing", IEEE Transactions on Image Processing, Vol. 5, No. 4, April 1996.
  11. Shyam Lal, Sanjeev Kumar and Mahesh Chandra, "Removal of High Density Salt & Pepper Noise Through Super Mean Filter for Natural Images", IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, No 3, May 2012.
  12. Ulrich Eckhardt, "Root Images of Median Filters — Semi-topological Approach", 11th International Workshop on Theoretical Foundations of Computer Vision Dagstuhl Castle, Germany, April 7–12, 2002 Revised Papers, pp176-195.
  13. R. H. Chan, C. W. Ho and M. Nikolova, "Salt-and-pepper noise removal by median-type noise detectors and detail preserving regularization", IEEE Transactions on Image Processing, vol. 14, no. 10, 2005, pp. 1479–1485.
  14. J. F. Traub," Computational Complexity of Iterative Processes", SI AM J. COMPUT. Vol. l, No. 2, June,1972.
Index Terms

Computer Science
Information Sciences

Keywords

Decision based algorithm Median Filter Recursive median filtering salt and pepper noise unsymmetrical trimmed median filter.