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

Illumination based Sub Image Histogram Equalization: A Novel Method of Image Contrast Enhancement

by Sangeeta Rani, Ashwini Kumar, Kuldeep Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 20
Year of Publication: 2015
Authors: Sangeeta Rani, Ashwini Kumar, Kuldeep Singh
10.5120/21183-4251

Sangeeta Rani, Ashwini Kumar, Kuldeep Singh . Illumination based Sub Image Histogram Equalization: A Novel Method of Image Contrast Enhancement. International Journal of Computer Applications. 119, 20 ( June 2015), 14-19. DOI=10.5120/21183-4251

@article{ 10.5120/21183-4251,
author = { Sangeeta Rani, Ashwini Kumar, Kuldeep Singh },
title = { Illumination based Sub Image Histogram Equalization: A Novel Method of Image Contrast Enhancement },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 20 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 14-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number20/21183-4251/ },
doi = { 10.5120/21183-4251 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:04:34.222286+05:30
%A Sangeeta Rani
%A Ashwini Kumar
%A Kuldeep Singh
%T Illumination based Sub Image Histogram Equalization: A Novel Method of Image Contrast Enhancement
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 20
%P 14-19
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A novel Illumination based Sub-Image Histogram Equalization (ISIHE) method for contrast enhancement for low illumination gray scale images is presented in this paper. As the main crux of paper, illumination thresholds are computed and used to divide the original image into sub-images of different intensity levels. To control the enhancement rate, the histogram is clipped using a threshold value that represents the average number of grey level occurrences in the image. Each individual sub histogram is equalized independently and all sub images are integrated into one complete image for analysis as a final step. The experimental results are compared with other Histogram Equalization (HE) methods and ISIHE has shown promising results.

References
  1. Gonzalez, R. C. , Woods, R. E. , 2002. Digital Image processing, second ed. Prentice Hall. .
  2. Kim, Y. T. , 1997. Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Trans. Consumer Electron. 43 (1), 1–8.
  3. Wongsritong, K. , Kittayaruasiriwat, K. . , F. , Cheevasuvit , K. , and Somboonkaew, A. , "Contrast Enhancement using Multipeak Histogram Equalization with Brightness Preserving", IEEE Asia-Pacific Conference on Circuits and Systems, (1998).
  4. Wang, Y. , Chen, Q. , Zhang, B. M. , 1999. Image enhancement based on equal area dualistic sub-image histogram equalization method. IEEE Trans. Consumer Electron. 45 (1), 68–75.
  5. Chen, S. D. , Ramli, A. R. , 2003. Minimum mean brightness error bi-histogram equalization in contrast enhancement. IEEE Trans. Consumer Electron. 49 (4), 1310–1319.
  6. Chen, S. D. , Ramli, A. R. , 2003. Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation. IEEE Trans. Consumer Electron. 49 (4), 1301–1309.
  7. Yang, S. , Oh, J. H. and Park, Y. , 2003. Contrast Enhancement using Histogram Equalization with Bin Underflow and Bin Overflow", International Conference on Image Processing ICIP-2003, vol. 1, 881-884.
  8. Wang, B. J. , Liu , S. Q. , Li, Q. and Zhou , H. X. , 2006. A real-time Contrast Enhancement Algorithm for Infrared Images based on Plateau Histogram", Infrared Physics & Technology, 48, 77-82.
  9. Sim, K. S. , Tso, C. P. , Tan, Y. Y. , 2007. Recursive sub-image histogram equalization applied to gray scale images. Pattern Recogn. Lett. 28 (10), 1209–1221.
  10. Wadud, M. A. , Kabir, M. H. , Dewan, M. A. A. , Chae, O. , 2007. A Dynamic Histogram Equalization for Image Contrast Enhancement, IEEE Trans. Consumer Electron. , 53, 593–600.
  11. Ibrahim, H. , Kong, N. S. P. , 2007. Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement, IEEE Trans. Consumer Electron. , 53,1752–1758
  12. Menotti, D. , Najman, L. , Facon , J. and Araujo, A. D. A. , 2007 . Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving, IEEE Transactions on Consumer Electronics, 53(3), 1186-1194.
  13. Sengee, N. and Choi, H. K. , 2008. Brightness preserving weight clustering histogram equalization, IEEE Transactions on Consumer Electronics, 54(3), 1329-1337.
  14. Kim, T. , Paik, J. , 2008. Adaptive contrast enhancement using gain-controllable clipped histogram equalization. IEEE Trans. Consumer Electron. 54 (4), 1803–1810.
  15. Ooi, C. H. , Kong, N. S. P. , Ibrahim, H. , 2009. Bi-histogram equalization with a plateau limit for digital image enhancement. IEEE Trans. Consumer Electron. 55 (4), 2072–2080.
  16. Ooi, C. H. , Isa, N. A. M. , 2010. Adaptive Contrast Enhancement Methods with Brightness Preserving, IEEE Trans. on Consumer Electron. , 56, 2543 - 2551.
  17. Liang, K. , Ma, Y. , Xie , Y. , Zhou, B. and Wang, R. , 2012. A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization, Infrared Physics & Technology, 55, 309-315.
  18. Singh, K. , Kapoor, R. , 2014. Image enhancement using Exposure based Sub Image Histogram Equalization, Pattern Recognition Letters , 36, 10 – 14
  19. Singh, K. , Kapoor, R. , 2014. Image enhancement via Median-Mean Based Sub-Image-Clipped Histogram Equalization, Optik, 125,4646-4651
Index Terms

Computer Science
Information Sciences

Keywords

Image Contrast Enhancement Image Illumination Threshold Histogram Equalization

Powered by PhDFocusTM