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Improved Median Filter using ROAD for Removal of Impulse Noise

by Rawat A. K, Singh J
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 94 - Number 7
Year of Publication: 2014
Authors: Rawat A. K, Singh J
10.5120/16357-5741

Rawat A. K, Singh J . Improved Median Filter using ROAD for Removal of Impulse Noise. International Journal of Computer Applications. 94, 7 ( May 2014), 29-33. DOI=10.5120/16357-5741

@article{ 10.5120/16357-5741,
author = { Rawat A. K, Singh J },
title = { Improved Median Filter using ROAD for Removal of Impulse Noise },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 94 },
number = { 7 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 29-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume94/number7/16357-5741/ },
doi = { 10.5120/16357-5741 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:17:01.717761+05:30
%A Rawat A. K
%A Singh J
%T Improved Median Filter using ROAD for Removal of Impulse Noise
%J International Journal of Computer Applications
%@ 0975-8887
%V 94
%N 7
%P 29-33
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper represents a new algorithm which uses a trimmed global mean filter with ROAD to remove random impulse noise. A two step algorithm is implemented in which the first step ensure detection of corrupted pixels in the degraded image and the second step replaces the degraded image with either the median of uncorrupted pixels in the selected window and if the selected window contains noisy pixels only than trimmed global mean filter is used. To avoid computational delay and to ensure a light algorithm, the selected window is fixed [3x3] in both the detection and the filtering stage. This algorithm outperforms many filters in restoring image corrupted by random value impulse noise.

References
  1. Chan, R. H. et al, (2004). "An iterative procedure for removing random-valued impulse noise", IEEE Signal Process. Lett. , Vol. 11, no. 12, pp. 921–924.
  2. Chen, T. et al, (2001b). "Space variant median filters for the restoration of impulse noise corrupted images," IEEE Trans. Circuits Syst. II,Analog Digit. Signal Process. , Vol. 48, no. 8, pp. 784–789.
  3. Luo, W. (2005). "A new efficient impulse detection algorithm for the removal of impulse noise", IEICE Trans. Fundam. , Vol. E88-A, no. 10, pp. 2579–2586.
  4. Kokaram, A. C. et al, (1995). "Detection of missing data in image sequences", IEEE Transaction on image processing, Vol. 4, no. 11, pp. 1496-1508.
  5. Srinivasan, K. S. et al, (2007). "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.
  6. Pratt, W. K. (1975). "Median filtering", Tech. Rep. , Image Proc. Inst. , Univ. , Southern California, Los Angeles.
  7. Vijaykumar, V. R. (2010). "Detection based adaptive median filter to remove blotches, scratches, streaks, stripes and impulse noise in images", Proceedings of 2010 IEEE 17th International conference on image processing, pp. 117-120.
  8. Garnett, R. et al, (2005). "A universal noise removal algorithm with impulse detector", IEEE transaction on image processing, Vol. 14, no. 11, pp. 1-7.
  9. Chen, T. et al, (2001a). "Adaptive impulse detection using center-weighted median filters", IEEE Signal Process. Lett. , Vol. 8, no. 1, pp. 1–3
  10. Crnojevic´ V. et al, (2004). "Advanced impulse detection based on pixel-wise MAD", IEEE Signal Process. Lett. , Vol. 11, no. 7, pp. 589–592.
  11. Tomasi, C. et al, (1998). "Bilateral filtering for colour and gray images", Sixth International Conference on Computer Vision, pp. 839-846.
  12. Nadenau, M. J. et al, (1996). "Blotches and scratch detection in image sequence based on rank ordered differences", proceedings of Int Workshop on time varying image processing and moving object recognition, Vol. 6, pp. 1-7.
  13. Subg-Jea, K. et al, (1991). "Center Weighted Median Filters and Their applications to image enhancement", IEEE Transactions on Circuits and Systems, Vol. 13, pp. 583-598.
  14. Abreu, E. et al, (1996a). "A simple method for the restoration of image corrupted by streaks", Proc. IEEE International Symposium on circuit and system, Atlanta, Vol. 2, pp. 730-733.
  15. Dong, Y. et al, (2007). "A detection statistic for random valued impulse noise", IEEE transaction on image processing, Vol. 16, no. 4, pp. 1112-1120.
  16. Aiswarya, K. et al, (2010). "A new and efficient algorithm for the removal of high density salt and pepper noise in images and videos", in second international conference on computer modeling and simulation, Vol. 4, pp. 409-413.
  17. Wang, Z. et al, (1999). "Progressive switching median filter for the removal of impulse noise from highly corrupted images", IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process. , Vol. 46, no. 1, pp. 78–80.
  18. Balasubramanian, S. et al, (2009). "An efficient Nonlinear cascade filtering algorithm for removal of high density salt and pepper noise in image and video sequence", Intl Conf on control, Automation, communication and Energy Conservation, pp. 1-6
  19. Pomalaza-Racz C. A. et al, (1984). "An adaptive nonlinear edge preserving filter", IEEE Trans. Acoust. , Speech, Signal Process. , Vol. ASSP-32, pp. 571–576.
  20. Hwang, H. et al, (1995). "Adaptive Median Filter: New Algorithms and Results", IEEE transaction on image processing, Vol. 4, no. 4, pp. 499-502.
  21. Veerakumar, T. (2012). " An approach to minimize very high density salt and pepper noise through trimmed global mean" International journal of computer application, Vol. 39, pp. 29-33.
  22. Gonzalez, R. C. et al, (2002). Digital image processing, Englewood cliffs, NJ: Prentice- Hall.
  23. Tomasi, C. et al, (1998). "Bilateral filtering for colour and gray images", Sixth International Conference on Computer Vision, pp. 839-846.
  24. Chan, R. H. et al, (2005). "Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization", IEEE Trans. Image Process. , Vol. 14, no. 10, pp. 1479–1485.
  25. Chen, T. et al, (1999). "Tri-state median filter for image denoising", IEEE Trans. Image Process. , Vol. 8, no. 12, pp. 1834–1838.
Index Terms

Computer Science
Information Sciences

Keywords

ROAD ROLD Impulse Noise Denoise

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