Details

Enhancement of Images Using Histogram Techniques

Gunjan Bansal

Research Scholar, Dept of Computer Science and Engineering, Calorx Teachers’ University, Ahmedabad

Dr. Sachin Yadav

Professor, Dept of Computer Science and Engineering, G L Bajaj Institute of Technology & Management, Greater Noida, UP

66-75

Vol: 8, Issue: 1, 2018

Receiving Date: 2017-12-26 Acceptance Date:

2018-01-20

Publication Date:

2018-02-15

Download PDF

Abstract

Image enhancement approaches adopting histogram equalization can be broadly categorized into classes of global and local equalization implementation. The former method conducts equalization over all image pixels concurrently. In a canonical implementation, the resultant image has a histogram resembling a linear transformation or stretching from its original image histogram. In spatial relationships between neighboring pixels were taken into consideration.

Keywords: image enhancement; histogram equalization; image quality measurement

References

  1. M. A. A. Wadud, M. H. Kabir and O. Chae, “A Spatially Controlled Histogram Equalization for Image Enhancement”, 23rd International Symposium on Computer and Information Sciences, ISCIS ‘08, (2008).
  2. D. Sheet, H. Garud, A. Suveer, M. Mahadevappa and J. Chatterjee, “Brightness Preserving Dynamic Fuzzy Histogram Equalization”, IEEE Transactions on Consumer Electronics, vol. 56, no. 4, (2010) November, pp. 2475-2480.
  3. M. Khan, E. Khan, and Z. A. Abbasi, “Weighted average multi segment histogram equalization for brightness preserving contrast enhancement”, IEEE International Conference on Signal Processing, Computer and Control, ISPCC, (2012).
  4. Y.-T. Kim, “Contrast enhancement using brightness preserving bi histogram equalization,” IEEE Trans. On Consumer Electronics, vol. 43, no. 1, pp. 1-8, Feb. 1997
  5. 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.
  6. C. Wang and Z. Ye, “Brightness preserving histogram equalization with maximum entropy: A variational perspective,” IEEE Trans. On Consumer Electronics, vol. 51, no. 4, pp. 1326-1334, Nov. 2005.
  7. C. Shannon, “A mathematical theory of communication,” Bell Syst. Tech. J., vol. 27, pp. 379-423, 1948.
  8. M. Luessi, M. Eichmann, G. Schuster, and A. Katsaggelos, “New results on efficient optimal multilevel image thresholding,” in IEEE International Conference on Image Processing, 2006, pp. 773-776.
  9. David Menotti, Laurent Najman, Jacques Facon, and Arnaldo de A. Araújo “Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving”
  10. G. Turk, “Generating textures on arbitrary surfaces using reaction diffusion,” Comput. Graph. 25, 289-298 (1991).
  11. D. J. Heeger and J. R. Bergen, “Pyramid-based texture analysis/synthesis,” in Proc. Computer Graphics, pp. 229-238, Los Angles, CA, August 6-11 (1995).
  12. J. P. Rolland, A. Goon, and L. Yu, “Synthesis of textured complex backgrounds,” Opt. Eng. 37(7), 2055-2063 (1998).
  13. J. P. Rolland and R. Strickland, “An approach to the synthesis of biological tissue,” Opt. Express 1(13), 414:423 (1997).
Back

Disclaimer: All papers published in IJRST will be indexed on Google Search Engine as per their policy.

We are one of the best in the field of watches and we take care of the needs of our customers and produce replica watches of very good quality as per their demands.