CFP last date
21 October 2024
Reseach Article

Fuzzy based Low Contrast Image Enhancement Technique by using Pal and King Method

by Ajay Kumar Gupta, Siddharth Singh Chouhan, Manish Shrivastava
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 141 - Number 6
Year of Publication: 2016
Authors: Ajay Kumar Gupta, Siddharth Singh Chouhan, Manish Shrivastava
10.5120/ijca2016909648

Ajay Kumar Gupta, Siddharth Singh Chouhan, Manish Shrivastava . Fuzzy based Low Contrast Image Enhancement Technique by using Pal and King Method. International Journal of Computer Applications. 141, 6 ( May 2016), 25-29. DOI=10.5120/ijca2016909648

@article{ 10.5120/ijca2016909648,
author = { Ajay Kumar Gupta, Siddharth Singh Chouhan, Manish Shrivastava },
title = { Fuzzy based Low Contrast Image Enhancement Technique by using Pal and King Method },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 141 },
number = { 6 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 25-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume141/number6/24790-2016909648/ },
doi = { 10.5120/ijca2016909648 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:43:00.009747+05:30
%A Ajay Kumar Gupta
%A Siddharth Singh Chouhan
%A Manish Shrivastava
%T Fuzzy based Low Contrast Image Enhancement Technique by using Pal and King Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 141
%N 6
%P 25-29
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the most interesting and challenging area in image processing research is to enhance low Contrast images. Many images may suffer from poor contrast and noise due to the inadequate lighting during image acquiring. So it is required to enhance the contrast of image as well as remove the noise that decreases image quality. This paper presents a fuzzy based enhancement technique for low contrast grayscale image. Proposed works transforms the gray scale image from spatial domain to fuzzy domain, then modify the fuzzy domain by using the pal king membership function which modify image from low contrast to high contrast, And finally, transforms the gray scale image from modified fuzzy domain back to spatial domain by using defuzzification method. The performances of the proposed method are compared with the other existing methods. The proposed method gives better quality enhanced image and needs minimum processing time rather than the other methods.

References
  1. Khairunnisa Hasikin and Nor Ashidi Mat Isa, 2012. “Enhancement of the low contrast image using fuzzy set theory”14th International Conference on Modelling and Simulation, IEEE.
  2. S.S. Bedi1, Rati Khandelwal2,” 2013. Various Image Enhancement Techniques- A Critical Review” International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 3, March 2013
  3. Raman Maini and Himanshu Aggarwal, Mar 2010. ”A Comprehensive Review of Image Enhancement Techniques” JOURNAL OF COMPUTING, VOLUME 2, ISSUE 3, ISSN 2151-9617.
  4. M. Hanmandlu and D. Jha, 2006. "An Optimal Fuzzy System for Color Image Enhancement," Image Processing, IEEE Transactions on, vol. 15, pp. 2956-2966.
  5. Manpreet Kaur, Jasdeep Kaur, Jappreet Kaur, 2011. ” Survey of Contrast Enhancement Techniques based on Histogram Equalization” (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, No. 7.
  6. L. A. Zadeh, 1973. "Outline of a New Approach to the Analysis of Complex Systems and Decision Processes," Systems, Man and Cybernetics, IEEE Transactions on, vol. SMC-3, pp. 28-44.
  7. H.D. Cheng, Huijuan Xu, 2000 “A novel fuzzy logic approach to contrast enhancement”, Pattern Recognition , 33 , 2000, 809-819.
  8. S.K. Naik, C.A. Murthy, 2003 “Hue-preserving color image enhancement without gamut problem”, IEEE Trans. Image Process.,12, 2003, 1591–1598.
  9. Madasu Hanmandlu, Senior Member, IEEE, Om Prakash Verma, Nukala Krishna Kumar, and Muralidhar Kulkarni, Aug 2009 “A Novel Optimal Fuzzy System for Color Image Enhancement Using Bacterial Foraging”, IEEE transactions on instrumentation and measurement, vol. 58, no. 8.
  10. Gang Li, Yala Tong,Xinping Xiao, 2011 “Adaptive Fuzzy Enhancement Algorithm of Surface Image based on Local Discrimination via Grey Entropy”, Elsevier Procedia Engineering 15 (2011) 1590 – 1594.
  11. Khairunnisa Hasikin and Nor Ashidi Mat Isa, 2012 “Enhancement of the low contrast image using fuzzy set theory”14th International Conference on Modelling and Simulation, IEEE.
  12. X.-Y. Wang, T. Wang, and J. Bu, 2011 "Color image segmentation using pixel wise support vector machine classification," Pattern Recognition, vol. 44, pp. 777-787.
  13. D.-l. Peng and A.-k. Xue, 2005 "Degraded image enhancement with applications in robot vision," in Systems, Man and Cybernetics, IEEE International Conference on, 2005, pp. 1837-1842 Vol. 2.
  14. E. E. Kerre and M. Nachtegael,2000 Fuzzy techniques in image processing: Physica-Verlag.
  15. Pal S K, King R A. 1981 “Image enhancement using smoothing with fuzzy sets”. IEEE Trans. Systems, Man & Cybernetics, 11(7): 494-501.
Index Terms

Computer Science
Information Sciences

Keywords

Defuzzification Fuzzy domain Membership Function Spatial Domain.