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Fuzzy based Image Enhancement using Attribute Preserving and Filtering Techniques

by Shaziya Siddiqui, Praveen Kumar, B. P. S. Senger
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 101 - Number 9
Year of Publication: 2014
Authors: Shaziya Siddiqui, Praveen Kumar, B. P. S. Senger
10.5120/17713-8129

Shaziya Siddiqui, Praveen Kumar, B. P. S. Senger . Fuzzy based Image Enhancement using Attribute Preserving and Filtering Techniques. International Journal of Computer Applications. 101, 9 ( September 2014), 10-14. DOI=10.5120/17713-8129

@article{ 10.5120/17713-8129,
author = { Shaziya Siddiqui, Praveen Kumar, B. P. S. Senger },
title = { Fuzzy based Image Enhancement using Attribute Preserving and Filtering Techniques },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 101 },
number = { 9 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 10-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume101/number9/17713-8129/ },
doi = { 10.5120/17713-8129 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:31:12.794569+05:30
%A Shaziya Siddiqui
%A Praveen Kumar
%A B. P. S. Senger
%T Fuzzy based Image Enhancement using Attribute Preserving and Filtering Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 101
%N 9
%P 10-14
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper a general framework for image improvement is proposed based on fuzzy logic with histogram modification for image improvement is bestowed. During this framework, image enhancement is posed as an improvement downside that minimizes a cost function. Histogram equalization is a good technique for image enhancement. However, a traditional histogram equalization (HE) typically leads to excessive contrast enhancement, By applying the fuzzy membership function the extent of various image attributes will be adjusted; noise lustiness, white/black stretching and mean-brightness preservation could simply be incorporated into the optimization. Conjointly a median filter of 5x5 is additionally incorporated with the fuzzy image enhancement system. The performance of the entire projected system is evaluated by applying it on different test images and therefore the results obtained are conferred. The aim of this paper is to reinforce the color images using the fuzzy filtering techniques. Image enhancement is employed to enhance the standard of a picture. The experiment is applied on varied pictures that prove that proposed image enhancement algorithms enhance poor quality pictures terribly effectively.

References
  1. Brinkman B. H. , Manduca A and Robb R. A. (1998) IEEE Transaction in Medical imaging, vol. 17, no. 2,pp. 161-171.
  2. Lee J (1980) IEEE Transaction on pattern analysis and machine intelligence, pp. 165-168.
  3. Polesel A (2000) IEEE Transaction on Image Processing, vol. 9, pp. 505-510.
  4. Buades A. , Coll B. and Morel J. (2006) Numerische Mathematik, 105, No. 1, pp. 1-34.
  5. Nagao M and Matsuyama T. (1997) Computer Graphics and Image Processing, vol. 9, pp. 394-407.
  6. Ming Zhang and Bahadur Gunturk (2008) ICASSP, IEEE, pp. 929-932.
  7. Mukesh C. Motwani, Mukesh C. Gadiya, Rakhi C. Motwani, Frederick C. Harris (2004) GSPx, Santa Clara Convention Center, Santa Clara, CA, pp, 27-30.
  8. Zhou Wang and Alan C. Bovik (2002) IEEE Signal Processing Letters, 9, No. 3.
  9. Lee J (1983) Graphics and Image Processing, vol. 24, pp. 255-269.
  10. T. chen and H. R Whu, "Space Space variant median filters for the restoration of impulse noise corrupted images"- IEEE Trans. Image processing vol-7 pp784-789 1998.
  11. P. Maragos and R. Schafer, "Morphological Filters–Part II: Their Relations to Median, Order Statistic, and Stack Filters", IEEE Trans. Acoust. , Speech, Signal Processing, vol. 35, no. 8, pp. 1170–1184, 1987.
  12. R. C. Gonzalez, R. E. Woods, "Digital Image Processing", 2ed, Prentice-Hall, 2002.
  13. Image enhancement-spatial domain, June 2004 [on line PDF]. http://depts. washington. edu/bicg/documents/BE244-Image-Enhancement. pdf
  14. Frequency Domain, May 2011 [on line PDF]. http://www. cs. umsl. edu/~sanjiv/classes/cs5420/lectures/freq. pdf
  15. Yeong-Taekgi M "Contrast Enhancement Using Brightness Preserving Bi-Histogram Equalization" IEEE Transactions on Consumer Electronics, Signal Processing, Vol. 43, Feb 1997.
  16. Khairunnisa Hasikin , Nor Ashidi Mat Isa , "Enhancement of the low contrast image using fuzzy set theory", 14th International Conference on Modelling and Simulation, pp. 371-376, 2012
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy Logic Image Processing Image Enhancement.

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