Research Article
A Comparative Study of the Performance of Wavelet Decomposition of Images using Kekre’s Transform vis-a-vis Haar and Daubechies
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 27 - Issue 6 |
| Published: August 2011 |
| Authors: Bijith Marakarkandy, Dr. B K Mishra |
10.5120/3304-4524
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Bijith Marakarkandy, Dr. B K Mishra . A Comparative Study of the Performance of Wavelet Decomposition of Images using Kekre’s Transform vis-a-vis Haar and Daubechies. International Journal of Computer Applications. 27, 6 (August 2011), 28-33. DOI=10.5120/3304-4524
@article{ 10.5120/3304-4524,
author = { Bijith Marakarkandy,Dr. B K Mishra },
title = { A Comparative Study of the Performance of Wavelet Decomposition of Images using Kekre’s Transform vis-a-vis Haar and Daubechies },
journal = { International Journal of Computer Applications },
year = { 2011 },
volume = { 27 },
number = { 6 },
pages = { 28-33 },
doi = { 10.5120/3304-4524 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2011
%A Bijith Marakarkandy
%A Dr. B K Mishra
%T A Comparative Study of the Performance of Wavelet Decomposition of Images using Kekre’s Transform vis-a-vis Haar and Daubechies%T
%J International Journal of Computer Applications
%V 27
%N 6
%P 28-33
%R 10.5120/3304-4524
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In recent years Image and Signal compression have been receiving a lot of attention by scientists and researchers in order to improve storage and transmission capabilities. In this study we have compared the performance of Kekre’s wavelet with other wavelets viz. Haar and Daubechies 2 with respect to energy in the Low-Low (LL ), Low-High (LH) ,High-Low (HL) and High-High (HH) bands. The energy distribution in each band is an indicator of the performance of the transform for image compression. It is found that the percentage of energy in the low-low band is equal for Kekre’s and Haar wavelet. The daubechies 2 wavelet although offers a slightly higher energy compaction but the tradeoff is that the order of the filter being higher and therefore computational burden increases.
References
- An Introduction to Wavelets available at http://www.amara.com/IEEEwave/IEEEwavelet.html, accessed on August 9, 2011.
- A.W.Galli, G.T.Heydt, P.F.Rebiero , Exploring the power of wavelet analysis,IEEE computer applicationsin power, October 1996.
- H. B. Kekre, Archan Athawale,Dipali Sadavarti, Algorithm to Generate Kekre’s Wavelet Transform from Kekre’s Transform,IJSET, June 2010.
- Subband coding of images, John W.Woods, Sean D. Oneil, IEEE transactions on acoustic speech and signal processing, vol - assp 34.
- Perfect reconstruction two-channel linear phase quadrature-mirror filter (QMF) bank using Kekre’s transform matrix, B.Marakarkandy, B.K.Mishra, pp 180-184 , ICWET 2011.
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