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Fuzzy Logic based Image De-noising and Enhancement for Grayscale Images

by Suraj Kamya, Madhuri Sachdeva
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 2
Year of Publication: 2013
Authors: Suraj Kamya, Madhuri Sachdeva
10.5120/12855-9355

Suraj Kamya, Madhuri Sachdeva . Fuzzy Logic based Image De-noising and Enhancement for Grayscale Images. International Journal of Computer Applications. 74, 2 ( July 2013), 5-9. DOI=10.5120/12855-9355

@article{ 10.5120/12855-9355,
author = { Suraj Kamya, Madhuri Sachdeva },
title = { Fuzzy Logic based Image De-noising and Enhancement for Grayscale Images },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 2 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 5-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number2/12855-9355/ },
doi = { 10.5120/12855-9355 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:41:08.737451+05:30
%A Suraj Kamya
%A Madhuri Sachdeva
%T Fuzzy Logic based Image De-noising and Enhancement for Grayscale Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 2
%P 5-9
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A picture is worth a thousand words. Trillions of digital images are used for different purposes in real life every day. Noise can corrupt the images in different ways which results in loss of information. Salt & Pepper is a form of noise which occurs randomly in an image as white and black pixels. Traditionally, median filter is used to remove this kind of noise but it introduces blurring in image which causes loss of small details. In this paper Fuzzy Logic based Adaptive Median Filter (FL-AMF) using MATLAB® is proposed which removes the noise effectively and also preserves small details. By introducing various densities of noise, performance of both filters are compared using PSNR & it is found that FL-AMF gives better results.

References
  1. R. C. Gonzalez and R. E. Woods. Digital Image Processing. Pearson, 2011
  2. S. N. Sivanandam, S. N. Deepa Principles of soft computing. John Wiley & Sons, Inc, 2009.
  3. Fuzzy Logic Tool Box user guide Matlab(R2009b)
  4. A. B. Badiru, J. Y. Cheung, Fuzzy Engineering Expert Systems. John Wiley & Sons, Inc.
  5. T. J. Ross, Fuzzy Logic with engineering applications. Wiley
  6. B. Jayaram, "Fuzzy Inference System based Contrast Enhancement", EUSFLAT-LFA2011
  7. H. Xu, "An Adaptive Fuzzy Switching filter for images corrupted by impulsive noise" Sixth international conference on Fuzzy systems and Knowledge Discovery, 2009.
  8. Y. Zhou, "Adaptive Fuzzy Median Filter for images corrupted by impulsive noise", Congress on Image and Signal Processing, 2008.
  9. S. Zhang and M. A. Karim, ?A new impulse detector for switching median filters?, IEEE Signal Processing Letters, vol 9, no 11, pp 360-363, Nov 2002.
  10. R. H. Chan, C. Ho, and M. Nikolova," Salt-and- Pepper Noise Removal by Median-type Noise Detectors and Detail- preserving Regularization," IEEE Transaction on Image Processing, Vol. 14, No. 10, Oct, 2005.
  11. K. M. Singh, "Fuzzy Rule based Median filter for Gray-Scale Images, ",Journal of information Hiding and Multimedia signal processing,vol. 2,no. 2, April 2011.
  12. H. Kundra," Filter for removal of impulse noise by using fuzzy logic", International Journal of image processing (IJIP), vol. 3, issue 3, March 2011.
  13. J. Kaur, "SALT & PEPPER NOISE REMOVAL USING FUZZY BASED ADAPTIVE FILTER", International Journal of Science, Engineering and Technology Research (IJSETR) Volume 1, Issue 1, July 2012.
  14. Z. F. Deng, Z. P. Yin, and Y. L. Xiong, "High probability impulse noise-removing algorithm based on mathematical morphology," IEEE Signal Process. Lett. , vol. 14, no. 1, pp. 31–34, Jan. 2007.
  15. Pei-Yin Chen, Chih-Yuan Lien, "An Efficient Edge-Preserving Algorithm for Removal of Salt-and-Pepper Noise", IEEE Signal Processing Letters, vol. 15, 2008.
Index Terms

Computer Science
Information Sciences

Keywords

FL-AMF Fuzzy Inference System PSNR Membership set

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