We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

A Comparative Analysis of Image Contrast Enhancement Techniques based on Histogram Equalization for Gray Scale Static Images

by Vinod Kumar, Rahul Raj Choudhary
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 21
Year of Publication: 2012
Authors: Vinod Kumar, Rahul Raj Choudhary
10.5120/7072-9588

Vinod Kumar, Rahul Raj Choudhary . A Comparative Analysis of Image Contrast Enhancement Techniques based on Histogram Equalization for Gray Scale Static Images. International Journal of Computer Applications. 45, 21 ( May 2012), 11-15. DOI=10.5120/7072-9588

@article{ 10.5120/7072-9588,
author = { Vinod Kumar, Rahul Raj Choudhary },
title = { A Comparative Analysis of Image Contrast Enhancement Techniques based on Histogram Equalization for Gray Scale Static Images },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 21 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number21/7072-9588/ },
doi = { 10.5120/7072-9588 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:38:10.381046+05:30
%A Vinod Kumar
%A Rahul Raj Choudhary
%T A Comparative Analysis of Image Contrast Enhancement Techniques based on Histogram Equalization for Gray Scale Static Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 21
%P 11-15
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Contrast enhancement of digital images is conveniently achieved by spreading out intensity values over the total range of values, known as Histogram Equalisation. Since the enhancement is defined as the processing of an image to achieve more suitable than original image, it is purely application dependent and well proved with the simulation results of various image enhancement techniques. In this paper, we evaluate the performance of different Histogram Equalization techniques proposed for gray scale static images. In order to evaluate, the performance of these techniques, are examined on the basis of AMBE, PSNR and Entropy metrics. In this process enhancement techniques are applied on the images with different sizes and received from different application fields like real images, medical images etc. It is well illustrated in this paper that Brightness Preserving Dynamic Histogram Equalization (BPDHE) is the most suitable technique in terms of mean brightness preservation as it has least average AMBE value. In terms of PSNR, MPHEBP is the most suitable technique because it has the highest average PSNR value. In terms of Entropy, BBHE and RSIHE(r=2) are the best techniques, since these have the highest average Entropy values. The performance of BPDHE is not satisfactory in terms of Entropy.

References
  1. R. Gonzalez and R. Woods, Digital Image Processing, 2nd ed. Prentice Hall, Jan. 2002.
  2. Freescale Semiconductor Document Number: AN4318
  3. Application Note Rev. 0, June 2011
  4. Yeong-Taeg Kim, "Contrast Enhancement using Brightness Preserving Bi-Histogram Equalization", IEEE Transactions on Consumer Electronics, vol. 43, no. 1, February 1997.
  5. Soong-Der Chen,Abd. Rahman Ramli, "Contrast Enhancement using Recursive Mean-Separate Histogram Equalization", IEEE Transactions on Consumer Electronics, vol. 49, no. 4, November 2003.
  6. K. S. Sim, C. P. Tso, Y. Y. Tan, "Recursive Sub-Image Histogram Equalization Applied to Gray Scale Images", Pattern Recognition Letters, vol. 28(2007),pp. 1209-1221.
  7. Soong-Der Chen and Abd. Rahman 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.
  8. K. Wongsritong, K. Kittayaruasiriwat, F. Cheevasuvit, K. Dejhan and A. Somboonkaew, "Contrast Enhancement using Multipeak Histogram Equalization with Brightness Preserving", IEEE Asia-Pacific Conference on Circuit and System, pp. 455-458, November 1998.
  9. Haidi Ibrahim and Nicholas Sia Pik Kong," Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement", IEEE Transactions on Consumer Electronics, vol. 53, no. 4, November 2007.
Index Terms

Computer Science
Information Sciences

Keywords

Performance Metrics Absolute Mean Brightness Error (ambe) Peak Signal To Noise Ratio (psnr) Entropy Contrast Enhancement Histogram Equalization