CFP last date
20 January 2025
Reseach Article

Image Compression using Fusion Technique and Quantization

by T. Rammohan, K. Sankaranarayan, Shalakha Rajan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 63 - Number 22
Year of Publication: 2013
Authors: T. Rammohan, K. Sankaranarayan, Shalakha Rajan
10.5120/10764-5382

T. Rammohan, K. Sankaranarayan, Shalakha Rajan . Image Compression using Fusion Technique and Quantization. International Journal of Computer Applications. 63, 22 ( February 2013), 7-11. DOI=10.5120/10764-5382

@article{ 10.5120/10764-5382,
author = { T. Rammohan, K. Sankaranarayan, Shalakha Rajan },
title = { Image Compression using Fusion Technique and Quantization },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 63 },
number = { 22 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 7-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume63/number22/10764-5382/ },
doi = { 10.5120/10764-5382 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:15:02.777815+05:30
%A T. Rammohan
%A K. Sankaranarayan
%A Shalakha Rajan
%T Image Compression using Fusion Technique and Quantization
%J International Journal of Computer Applications
%@ 0975-8887
%V 63
%N 22
%P 7-11
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper describes a method for image compression using a fusion technique: combining wavelet transform and curvelet transform. Both the transforms when used individually shows some disadvantages. Wavelets though optimal for point singularities have limitations with directional properties. Similarly curvelets are challenged with small features. By combining both the transforms , the number of bits used to represent the image is reduced. The coefficients obtained after applying fusion technique is then selected for quantization and encoding. Quantization chosen is vector quantization as it saves time compared to scalar quantization. Vector quantization, mapping of image pixel intensity vectors into binary vectors. Arithmetic encoding technique is employed. This method is effective to remove redundancy in encoding of data. This technique works fairly well for grayscale as well as colour images

References
  1. Mansoor, A. ; Mansoor, A. B. ; "On Image Compression using Digital Curvelet Transform", 9th International Multitopic Conference, Page (s): 1 – 4, IEEE INMIC 2005
  2. Howard, P. G. ; Vitter, J. S. ; "Arithmetic Coding For Data Compression"
  3. T. Rammohan and K. Sankaranarayanan, "An Advanced Curvelet Transform Based Image Compression Using Dead zone Quantization", in EJSR, Vol. 79 No: 4 (2012)
  4. Cosman, P. C. ; et al. ; "Using Vector Quantization For Image Processing", in Proceedings of IEEE , Vol. 81, No; 9 (1993)
  5. Gonzalez & Woods, "Digital Image Processing", Pearson Education, 2002.
  6. Anil K. Jain, "Fundamentals of Digital Image Processing", Prentice Hall, 2000.
  7. Cosman P. C. ; et al. ; "Vector Quantization of Image Subbands: A Survey", IEEE Trans. On Image Processing, Vol. 5, No; 2 (1996)
  8. Boopathy. G & Arockyasamy . S, "Implementation of Vector Quantization for Image Compression", Global Journal of Computer science & Technology, Vol. 10, Issue. 3 (2010)
  9. Said . A, "Introduction to Arithmetic Coding-Theory & Practice", Imaging Systems Laboratory, (2004)
  10. M. Sifuzzaman et al, "Application of Wavelet Transform and its Advantages Compared to Fourier Transform", Journal of Physical Sciences, VOL. 13, 2009.
  11. Marc Antonini et al. "Image Coding using Wavelet Transform", IEEE Transactions on image processing , Vol. 1, No. 2, April 1992.
  12. Arokia Priya. R et al. "Dual Tree Wavelet Transforms in Image Compression", International Journal of Engineering Sciences Research (IJESR), VOL. 1, NO. 1, 2011.
  13. Kiruthika. P and Thirumaraiselvi. C, "Image Compression Using Hybrid Method of Easy Path Wavelet Transform", VOL. 2, Special Issue 1, Bonfring International Journal of Advances in Image Processing, 2012.
  14. Mikhail Shnaider and Andrew P Paplinski, "Wavelet Transform in Image Coding", Department of Robotics and Technology, Monash University, OCTOBER 19, 1994
  15. M. S. Joshi et al, "Image Compression Using Curvelet, Ridgelet and Wavelet Transform, A Comparative Study" ICGST-GVIP, ISSN 1687-398X, VOL. 8, Issue (III), October 2008
Index Terms

Computer Science
Information Sciences

Keywords

Image compression curvelet transform wavelet transform quantization encoding