We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Reseach Article

Fuzzy Hybrid Filtering Techniques for Removal of Random Noise from Medical Images

by R.Marudhachalam, Gnanambal Ilango
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 38 - Number 1
Year of Publication: 2012
Authors: R.Marudhachalam, Gnanambal Ilango
10.5120/4651-6732

R.Marudhachalam, Gnanambal Ilango . Fuzzy Hybrid Filtering Techniques for Removal of Random Noise from Medical Images. International Journal of Computer Applications. 38, 1 ( January 2012), 15-18. DOI=10.5120/4651-6732

@article{ 10.5120/4651-6732,
author = { R.Marudhachalam, Gnanambal Ilango },
title = { Fuzzy Hybrid Filtering Techniques for Removal of Random Noise from Medical Images },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 38 },
number = { 1 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 15-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume38/number1/4651-6732/ },
doi = { 10.5120/4651-6732 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:24:25.024319+05:30
%A R.Marudhachalam
%A Gnanambal Ilango
%T Fuzzy Hybrid Filtering Techniques for Removal of Random Noise from Medical Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 38
%N 1
%P 15-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Reducing or removing random noise from medical image is a very active research area in medical image processing. In recent years, technological development has significantly improved in analyzing medical images. This paper proposes various fuzzy hybrid filtering techniques for the removal of random noise from medical images, by topological approach. Each of these fuzzy filters, which apply a weighted membership function to an image within a 8-neighbours of a point, is simple and easy to implement. The quality of the noise reduction in images is measured by the statistical quantity measures: Root Mean Square Error (RMSE) and Peak Signal-to-Noise Ratio (PSNR). The performances of these fuzzy filters on images tainted with low, medium and high random noise are compared with various existing filtering techniques.

References
  1. . Tukey J.W, Nonlinear (nonsuperposable) methods for smoothing data, in Proc. Congr. Rec. EASCOM ’74, (1974),673-681Tavel, P. 2007 Modeling and Simulation Design. AK Peters Ltd.
  2. . Kwan H. K and Cai Y.,Median filtering using fuzzy concept, Proceedings of 36th Midwest Symposium on Circuits and Systems, Vol.2, (1993),824-827.
  3. . Kwan, H.K., Cai Y., Fuzzy filters for image filtering, presented at Midwestern Symposium on Circuits and Systems, (2002),III672-III675.
  4. . Nachtegael M,Van der Weken D, Van De Ville A, Derre E, Philips W, Lemahieu I, An overview of fuzzy filters for noise reduction, Proceedings of IEEE International conference on Fuzzy systems, (2001),7-10.
  5. . Nachtegael M,Van der Weken D, Van De Ville A, Derre E, Philips W, Lemahieu I, A comparative study of classical and fuzzy filters for noise reduction, Proceedings of IEEE International conference on Fuzzy systems, (2001),11-14.
  6. . Schulte, S., Nachtegael, M., De Witte, V., Van der Weken, D., Kerre, E.E., A Fuzzy Impulse Noise Detection and Reduction Method. IEEE Transactions on Image Processing 15(5), (2006),1153-1162.
  7. . Gnanambal Ilango and Marudhachalam R, New hybrid filtering techniques for removal of Gaussian noise from medical images, ARPN Journal of Engineering and Applied Sciences, Vol 6, No.2, (2011),8-12.
  8. . Aneesh Agrawal, Abha Choubey and Kapil Kumar Nagwanshi, Development of adaptive fuzzy based Image Filtering techniques for efficient Noise Reduction in Medical Images, International Journal of Computer Science and Information Technologies Vol. 2(4),(2011),1457-1461
  9. . Gunamani Jena and R Baliarsingh, Suppression of Random Valued Impulsive Noise using Adaptive Threshold, International Journal of Latest Trends in Computing Vol.1.(2010),116-120.
  10. . Rosenfeld A, Digital topology, Amer. Math. Monthly 86, (1979),621–630.
  11. . Gonzalez. R and Woods. R, Digital Image Processing, Adison -Wesley, New York(1992).
  12. . Kerre E E and Nachtegael M. Editors, Fuzzy Techniques in image processing, Series on Studies in Fuzziness and Soft Computing, Vol.52, (2000), Springer-Verlog.
Index Terms

Computer Science
Information Sciences

Keywords

Ultrasound Medical Image Fuzzy hybrid filters Random noise Noise reduction