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Image Compression using Orthogonal Wavelets Viewed from Peak Signal to Noise Ratio and Computation Time

by P.m.k. Prasad, Prabhakar Telagarapu, G. Uma Madhuri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 4
Year of Publication: 2012
Authors: P.m.k. Prasad, Prabhakar Telagarapu, G. Uma Madhuri
10.5120/7177-9828

P.m.k. Prasad, Prabhakar Telagarapu, G. Uma Madhuri . Image Compression using Orthogonal Wavelets Viewed from Peak Signal to Noise Ratio and Computation Time. International Journal of Computer Applications. 47, 4 ( June 2012), 25-34. DOI=10.5120/7177-9828

@article{ 10.5120/7177-9828,
author = { P.m.k. Prasad, Prabhakar Telagarapu, G. Uma Madhuri },
title = { Image Compression using Orthogonal Wavelets Viewed from Peak Signal to Noise Ratio and Computation Time },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 4 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 25-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume47/number4/7177-9828/ },
doi = { 10.5120/7177-9828 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:41:01.428110+05:30
%A P.m.k. Prasad
%A Prabhakar Telagarapu
%A G. Uma Madhuri
%T Image Compression using Orthogonal Wavelets Viewed from Peak Signal to Noise Ratio and Computation Time
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 4
%P 25-34
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Uncompressed image data requires considerable storage capacity and transmission bandwidth. Despite rapid progress in mass-storage density, processor speeds, and digital communication system performance, demand for data storage capacity and data transmission bandwidth continues to outstrip the capabilities of available technologies. Images require substantial storage and transmission resources, thus image compression is advantageous to reduce these requirements. Different wavelets will be used to carry out the transform of test image and the results will be analyzed in terms of Peak signal to noise ratio obtained and the computation time taken for decomposition and reconstruction. The orthogonal wavelet used are Daubechies family of Haar (Daubechies 1), Daubechies 2, Daubechies 3, Daubechies 4, Daubechies 5, and Coiflet families, as well as Symlet families. . The wavelet which has the highest PSNR in each family is Haar(db),Coiflet1,andSymlet 2 and less computation time in each family is Haar(db1), symlet3, 4, 6 and coiflet1.

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Index Terms

Computer Science
Information Sciences

Keywords

Compression Image Wavelet Decomposition Level Psnr

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