CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Study on Various Techniques of Image Enhancement

by Sandeep Kaur, Parveen Kumar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 158 - Number 10
Year of Publication: 2017
Authors: Sandeep Kaur, Parveen Kumar
10.5120/ijca2017912819

Sandeep Kaur, Parveen Kumar . Study on Various Techniques of Image Enhancement. International Journal of Computer Applications. 158, 10 ( Jan 2017), 11-13. DOI=10.5120/ijca2017912819

@article{ 10.5120/ijca2017912819,
author = { Sandeep Kaur, Parveen Kumar },
title = { Study on Various Techniques of Image Enhancement },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 158 },
number = { 10 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 11-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume158/number10/26940-2017912819/ },
doi = { 10.5120/ijca2017912819 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:04:24.932542+05:30
%A Sandeep Kaur
%A Parveen Kumar
%T Study on Various Techniques of Image Enhancement
%J International Journal of Computer Applications
%@ 0975-8887
%V 158
%N 10
%P 11-13
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper has discuss the various techniques for image enhancement i.e histogram equalization, Brightness preserving bi-histogram equalization(BBHE), Dualistic Sub-Image Histogram Equalization (DSIHE), Minimum Mean Brightness Error Bi-HE Method (MMBEBHE), Recursive Mean –Separate HE Method (RMSHE),Mean brightness preserving histogram equalization(MBPHE).As well as it represents the comparison between the various techniques that shows the image enhances the overall contrast and visibility of local details. The review has shown that contrast enhancement approach based on dominant brightness level analysis and adaptive intensity transformation for remote sensing images.

References
  1. Manpreet Kaur, Jasdeep Kaur, Jappreet Kaur , Survey of Contrast Enhancement Techniques based on Histogram Equalization, 2011, Vol. 2 No. 7,pp 136
  2. Yeong-Taeg Kim , “Contrast Enhancement using Brightness Preserving Bi- Histogram equalization”, IEEE trans. on consumer Electronics, Vol. 43 , 1998.
  3. Y. Wang, Q. Chen, and B. Zhang, “Image enhancement based on equal area dualistic sub-image histogram equalization method,” IEEE Trans. on Consumer Electronics, vol. 45, no. 1, pp. 68-75, Feb. 1999.
  4. S.-D. Chen and A. Ramli, “Minimum mean brightness error Bi-Histogram equalization in contrast enhancement,” IEEE Trans. on ConsumerElectronics, vol. 49, no. 4, pp. 1310-1319, Nov. 2003
  5. 2007.
  6. Kanwal, N., Girdhar, A. and Gupta, S., 2011, May. Region based adaptive contrast enhancement of medical x-ray images. In Bioinformatics and Biomedical Engineering,(iCBBE) 2011 5th International Conference on (pp. 1-5). IEEE.
  7. Ehsani, S.P., Mousavi, H.S. and Khalaj, B.H., 2011, November. Chromosome image contrast enhancement using adaptive, iterative histogram matching. In 2011 7th Iranian Conference on Machine Vision and Image Processing (pp. 1-5). IEEE.
  8. Ke, W.M., Chen, C.R. and Chiu, C.T., 2011. BiTA/SWCE: Image enhancement with bilateral tone adjustment and saliency weighted contrast enhancement. IEEE Transactions on Circuits and Systems for Video Technology, 21(3), pp.360-364.
  9. Jha, R.K., Chouhan, R., Biswas, P.K. and Aizawa, K., 2012, September. Internal noise-induced contrast enhancement of dark images. In 2012 19th IEEE International Conference on Image Processing (pp. 973-976). IEEE.
  10. Jha, R.K., Chouhan, R. and Biswas, P.K., 2012, February. Noise-induced contrast enhancement of dark images using non-dynamic stochastic resonance. In Communications (NCC), 2012 National Conference on (pp. 1-5). IEEE.
  11. Lee, E., Kim, S., Kang, W., Seo, D. and Paik, J., 2013. Contrast enhancement using dominant brightness level analysis and adaptive intensity transformation for remote sensing images. IEEE Geoscience and remote sensing letters, 10(1), pp.62-66.
  12. Chouhan, R., Jha, R.K. and Biswas, P.K., 2013. Enhancement of dark and low-contrast images using dynamic stochastic resonance. IET Image Processing, 7(2), pp.174-184.
  13. Kil, T.H., Lee, S.H. and Cho, N.I., 2013, May. A dehazing algorithm using dark channel prior and contrast enhancement. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 2484-2487). IEEE.
  14. Pal, S.K. and King, R.A., 1980. Image enhancement using fuzzy set. Electronics letters, 16, pp.376-378
  15. Chen, X. and Lv, L., 2013, November. A Compositive Contrast Enhancement Algorithm of IR Image. In Information Technology and Applications (ITA), 2013 International Conference on (pp. 58-62). IEEE.
  16. Maragatham, G., and S. Md Mansoor Roomi. "An automatic contrast enhancement method based on stochastic resonance." In 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), pp. 1-7. IEEE, 2013.
  17. Celik, T., 2014. Spatial entropy-based global and local image contrast enhancement. IEEE Transactions on Image Processing, 23(12), pp.5298-5308.
  18. Cao, G., Zhao, Y., Ni, R. and Li, X., 2014. Contrast enhancement-based forensics in digital images. IEEE transactions on information forensics and security, 9(3), pp.515-525.
Index Terms

Computer Science
Information Sciences

Keywords

Image enhancement different techniques of image enhancement HE BBHE DSIHE MMBEBHE RMSHE MBPHE and Comparison table

Powered by PhDFocusTM