Call for Paper - March 2020 Edition
IJCA solicits original research papers for the March 2020 Edition. Last date of manuscript submission is February 20, 2020. Read More

Histogram Equilization on Wavelet based Compression Techniques

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 98 - Number 14
Year of Publication: 2014
Sandeep Dalal
Poonam Rani

Sandeep Dalal and Poonam Rani. Article: Histogram Equilization on Wavelet based Compression Techniques. International Journal of Computer Applications 98(14):1-5, July 2014. Full text available. BibTeX

	author = {Sandeep Dalal and Poonam Rani},
	title = {Article: Histogram Equilization on Wavelet based Compression Techniques},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {98},
	number = {14},
	pages = {1-5},
	month = {July},
	note = {Full text available}


This paper analyzes the effect of histogram equalization on the wavelet based compression techniques. Image compression is reducing the size of an image using one of the encoding techniques. Encoding helps in saving disk space by representing the same data in lesser number of bytes. Histogram is a graphical representation of intensity distribution of an image. It expresses the number of pixel values for each intensity value of an image. Histogram Equalization is a method used to improve the contrast of an image to stretch out the full range of an intensity . Comparison among algorithms has been made with respect to PSNR (Peak signal to noise ratio), MSE (Mean square error), MAE (Mean Absolute Error), L2RAT, Compression ratio.


  • Fundamental Data Compression ,By Ida Mending PuButter worth-Heinemann ,English , 2205 , ISBN 0750663103.
  • Digital Image Processing ,By Jayaraman.
  • Ms. S. Gupta, Mr. S. S. Purkayastha, Image Enhancement and Analysis of Microscopic Images using Various Image Processing Techniques, International Journal of Engineering Research and Applications (IJERA), Vol. 2, Issue 3, May-Jun 2012 .
  • R. G. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed. Publishing House of Electronics Industry, Beijing, pp. 129, 142, 174-176, 178.
  • Shapiro J. M. Embedded image coding using zero trees of wavelet coefficients. IEEE Trans. Signal Proc. , Vol. 41, No. 12, pp. 3445 (3462, 1993).
  • A. Said,W. A. Pearlman. A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Trans. on Circuits and Systems for Video Technology, Vol. 6, No. 3, pp. 243 -250, 1996.
  • Y. Yuan, M. K. Mandal. Novel embedded image coding algorithms based on wavelet difference reduction, in: Proceedings of IEEE International Conference on Vision
  • Image Processing: The Fundamentals, Second Edition Maria Petrou and Costas Petrou 2010 John Wiley Sons, Ltd. ISBN: 978-0-470-74586-1
  • http://www. ni. com/white-paper/13306/en/
  • http://www. wikipedia. org
  • http://www. mathworks. in/help/wavelet/ref/mease. html
  • http://202. 3. 77. 50/ opticalv/interferometry/image
  • Image Enhancement Problem, use the following site http://www. fke. utm/lab/dsp/file/Uji1Problem. pdf
  • Fari Muhammad Abubakar. "Image Enhancement using Histogram Equalization and Spatial Filtering",International Journal of Science and Research (IJSR), India Online ISSN: 2319- 7064,Volume 1 Issue 3, December 2012