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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
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Index Terms

Computer Science
Information Sciences

Keywords

Image compression curvelet transform wavelet transform quantization encoding