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

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Iterative Thresholded Bi-Histogram Equalization for Medical Image Enhancement

by Qadar Muhammad Ali, Zhaowen Yan, Hua Li
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 114 - Number 8
Year of Publication: 2015
Authors: Qadar Muhammad Ali, Zhaowen Yan, Hua Li
10.5120/19999-1753

Qadar Muhammad Ali, Zhaowen Yan, Hua Li . Iterative Thresholded Bi-Histogram Equalization for Medical Image Enhancement. International Journal of Computer Applications. 114, 8 ( March 2015), 20-27. DOI=10.5120/19999-1753

@article{ 10.5120/19999-1753,
author = { Qadar Muhammad Ali, Zhaowen Yan, Hua Li },
title = { Iterative Thresholded Bi-Histogram Equalization for Medical Image Enhancement },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 114 },
number = { 8 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 20-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume114/number8/19999-1753/ },
doi = { 10.5120/19999-1753 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:52:10.910229+05:30
%A Qadar Muhammad Ali
%A Zhaowen Yan
%A Hua Li
%T Iterative Thresholded Bi-Histogram Equalization for Medical Image Enhancement
%J International Journal of Computer Applications
%@ 0975-8887
%V 114
%N 8
%P 20-27
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Enhancement of human vision to get an insight to information content is of vital importance. The traditional histogram equalization methods have been suffering from amplified contrast with the addition of artifacts and a surprising unnatural visibility of the processed images. In order to overcome these drawbacks, this paper proposes interative, mean, and multi-threshold selection criterion with plateau limits, which consist of histogram segmentation, clipping and transformation modules. The histogram partition consists of multiple thresholding processes that divide the histogram into two parts, whereas the clipping process nicely enhances the contrast by having a check on the rate of enhancement that could be tuned. Histogram equalization to each segmented sub-histogram provides the output image with preserved brightness and enhanced contrast. Results of the present study showed that the proposed method efficiently handles the noise amplification. Further, it also preserves the brightness by retaining natural look of targeted image.

References
  1. Y. Kim. 1997," Contrast enhancement using brightness preserving bi-histogram equalization", IEEE Transactions on Consumer Electronics , 43(1): 1-8
  2. Y. Wang, Q. Chen, B. Zhang, 1999," Image enhancement based on equal area dualistic sub-image histogram equalization method" IEEE Transactions on Consumer Electronics, 45(1): 68 - 75
  3. S. Chen, A. Ramli, 2003 "Minimum mean brightness error bi-histogram equalization in contrast enhancement" IEEE Transactions on Consumer Electronics, 49(4): 1310–1319
  4. C. Ooi, N. Sia, P. Kong, H. Ibrahim, 2009 "Bi-Histogram Equalization with a Plateau Limit for Digital Image Enhancement", 55(4): 2072–2080
  5. S. Lim, N. Isa, C. Ooi, K. Toh, 2013 "A new histogram equalization method for digital image enhancement and brightness preservation" Signal, Image Video Processing.
  6. C. Zuo, Q. Chen, X. Sui, 2013 "Range Limited Bi-Histogram Equalization for image contrast enhancement" Optik, 124(5): 425–431
  7. K. Singh, R. Kapoor, 2014 Image enhancement using Exposure based Sub Image Histogram Equalization" Pattern Recognition Letters, 36: 10–14.
  8. Ostu, N. , 1979 "A threshold selection method from gray level histogram" IEEE Trans. System Man Cybernet, SMC-8: 62–66
  9. D. Menotti Gomes, 2008, "Contrast enhancement in digital imaging using histogram equalization", phd dissertation Federal University of Minas Gerais, Graduate Program in Computer Science.
  10. S. Yang, J. Oh, Y. Park, 2003 "Contrast Enhancement Using Histogram with Bin Underflow and Bin Overflow" Proceedings of ICIP 03, 1: 881 – 884.
  11. Q. Wang, R. Ward ,2007 "Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization" IEEE Transactions on Consumer Electronics, 53(2): 757–764
  12. T. Kim, J. Paik, 2008 "Adaptive contrast enhancement using gain-controllable clipped histogram equalization" IEEE Transactions Consumer on Electronics, 54(4): 1803–1810
  13. Kapur N. , 1994 "Measures of Information and Their Applications" J. Wiley & Sons.
  14. R. Gonzalez, R. Woods, B. R. Masters, 2009 "Digital Image Processing", Third Edition, J. Biomed. Opt. , 14(2): 029901
  15. T. Arici, S. Dikbas,Y. Altunbasak, 2009 "A histogram modification framework and its application for image contrast enhancement". IEEE Transactions on Image Processing,1921–1935
  16. S. D. Chen, 2002 "A new image quality measure for assessment of histogram equalization-based contrast enhancement techniques" Digital Signal Processing, 22(4): 640–647
  17. Z. Wang, S. Member, A. C. Bovik , 2002 "A Universal Image Quality" Index, 9(3): 81–84
  18. A. Grigoryan, M. Grigoryan, 2009 "Brief Notes in Advanced DSP Fourier Analysis with MATLAB®", CRC Press.
  19. G. Simone, M. Pedersen, J. Hardeberg, 2012 "Measuring perceptual contrast in digital images" , Journal of Visual Communication and Image Representation, 23(3): 491–506
  20. S. Chen, A. Ramli, 2003 "Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation", IEEE Transactions on Consumer Electronics, 49(4): 1301–1309
  21. M. Rabbani, Paul W. Jones, 1991 "Digital Image Compression Techniques", SPIE Publications.
  22. K. Sim, C. Tso, Y. Tan, 2007 "Recursive sub-image histogram equalization applied to gray scale images", Pattern Recognition Letters, 28(10): 1209–1221
Index Terms

Computer Science
Information Sciences

Keywords

Bi-Histogram Equalization contrast enhancement Absolute mean brightness error (AMBE) Iterative Threshold Selection Brightness preserving with Plateau limit (ITSBPL) Multi-Value Selection (MVBPL) Mean Threshold Selection (MSBPL).

Powered by PhDFocusTM