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Contrast Enhancement using Improved Adaptive Gamma Correction with Weighting Distribution Technique

by Seema Rani, Manoj Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 101 - Number 11
Year of Publication: 2014
Authors: Seema Rani, Manoj Kumar
10.5120/17735-8849

Seema Rani, Manoj Kumar . Contrast Enhancement using Improved Adaptive Gamma Correction with Weighting Distribution Technique. International Journal of Computer Applications. 101, 11 ( September 2014), 47-53. DOI=10.5120/17735-8849

@article{ 10.5120/17735-8849,
author = { Seema Rani, Manoj Kumar },
title = { Contrast Enhancement using Improved Adaptive Gamma Correction with Weighting Distribution Technique },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 101 },
number = { 11 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 47-53 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume101/number11/17735-8849/ },
doi = { 10.5120/17735-8849 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:31:26.395706+05:30
%A Seema Rani
%A Manoj Kumar
%T Contrast Enhancement using Improved Adaptive Gamma Correction with Weighting Distribution Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 101
%N 11
%P 47-53
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the important techniques in digital image processing is to enhance images. Contrast enhancement is a method that is used to enhance images for viewing process or for further analysis of images. Main idea behind contrast enhancement techniques is to increase contrast and to preserve original brightness of images. In this paper a contrast enhancement technique is proposed that first segments histogram of image recursively and then applies Adaptive Gamma Correction with Weighting Distribution (AGCWD) Technique. The proposed technique is basically an improvement over AGCWD technique and aims to get better contrast enhancement and brightness preservation than AGCWD technique.

References
  1. R. He, S. Luo, Z. Jing and Y. Fan, "Adjustable Weighting Image Contrast Enhancement Algorithm and its Implementation," IEEE Conference on Industrial Electronics and Applications, pp. 1750-1754, 21-23 June 2011.
  2. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall, Upper Saddle River, New Jersey, 2nd Edition, 2002.
  3. S. C. Huang, F. C. Cheng and Y. S. Chiu, "Efficient Contrast Enhancement using Adaptive Gamma Correction with Weighting Distribution," IEEE Transactions on Image Processing, Vol. 22, No. 3, pp. 1032-1041, March 2013.
  4. Y. T. Kim, "Contrast enhancement using brightness preserving bi-histogram equalization," IEEE Transactions On Consumer Electronics, Vol. 43, No. 1, pp. 1-8, February 1997.
  5. Y. Wang, Q. Chen, B. Zhang, "Image enhancement based on equal area dualistic sub-image histogram equalization method," IEEE Transactions on Consumer Electronics, Vol. 45, No. 1, pp. 68-75, February 1999.
  6. S. D. Chen, A. R. Ramli, "Minimum mean brightness error bi histogram equalization in contrast enhancement," IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, pp. 1310-1319, November 2003.
  7. S. D. Chen, A. R. Ramli, "Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation," IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, pp. 1301-1309, November 2003,
  8. C. Wang, Z. Ye, "Brightness preserving histogram equalization with maximum entropy: a variational perspective," IEEE Transactions on Consumer Electronics, Vol. 51, No. 4, pp. 1326-1334, November 2005.
  9. K. S. Sim , C. P. Tso, Y. Y. Tan, "Recursive sub image histogram equalization applied to gray scale images," Pattern Recognition Letters, Vol. 28, No. 10, pp. 1209-1221, july 2007.
  10. M. Kim, M. G. Chung, "Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement," IEEE Transactions on Consumer Electronics, Vol. 54, No. 3, pp. 1389-1397, August 2008.
  11. Z. G. Wang, Z. H. Liang, C. L. Liu, "A real time image processor with combining dynamic contrast ratio enhancement and inverse gamma correction for PDP," Displays, Vol. 30, Issue 3, pp 133-139, July 2009.
  12. T. Celik, T. Tjahjadi, "Contextual and variational contrast enhancement," IEEE Transactions on Image Processing, Vol. 20, No. 12, pp. 3431-3441, December 2011.
  13. S. Ashish, S. Rajeev, P. Yogadhar, "An exhaustive analysis on various foggy image enhancement techniques," International Journal of Advanced Research in Computer Science and Electronics Engineering, Vol. 3, No. 1, pp. 11-17, January 2014.
  14. S. Mohanram, B. Aarthi, C. Silambarasan, T. Joyce Selva Hephzibah, "An optimized image enhancement of foggy images using gamma adjustment," International Journal Of Advanced Research In Electronics And Communication Engineering, Vol. 3, No. 2, pp. 155-159, February 2014.
  15. R. Chauhan, S. S. Bhadoria, "An improved image contrast enhancement based on histogram equalization and brightness preserving weight clustering histogram equalization," International Conference on Communication Systems and Network Technologies, pp. 597-600, 3-5 June 2011.
  16. O. Marques, Practical Image and Video Processing using MATLAB, John Wiley and Sons, Hoboken, New Jersey, 1st Edition, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Histogram Equalization Recursive Segmentation Histogram Modification Gamma Correction Weighting Distribution.

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