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Analysis of Image Compression using Wavelets

by Vikas Pandey
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 17
Year of Publication: 2014
Authors: Vikas Pandey
10.5120/18291-8997

Vikas Pandey . Analysis of Image Compression using Wavelets. International Journal of Computer Applications. 103, 17 ( October 2014), 1-8. DOI=10.5120/18291-8997

@article{ 10.5120/18291-8997,
author = { Vikas Pandey },
title = { Analysis of Image Compression using Wavelets },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 17 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number17/18291-8997/ },
doi = { 10.5120/18291-8997 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:47.592367+05:30
%A Vikas Pandey
%T Analysis of Image Compression using Wavelets
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 17
%P 1-8
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper significant features of wavelet transform in compression of images, including the extent to which the quality of image is degraded by the process of wavelet compression and decompression is being studied it has been found that maximum improvement in picture quality with higher compression ratio is achieved by wavelet based image compression In this paper examined a basic concept of wavelets; wavelet transform and discrete wavelet transform and also deliberate the principle of image compression and image methodology. The objective is to select the appropriate mother wavelet during the transform stage towards compression the gray image and the quality of reconstructed image has been estimated in terms of image quality metrics PSNR and CR and also computes compression ratio at different level of decompositions of DWT. Haar, Daubechies and Biorthogonal, Coiflets and Symlet wavelet have been applied to an image and their qualitative and quantitative analysis results has been compared in terms of PSNR values, MSE and compression ratios. In this paper going to reduce the size of gray image with maintain good picture quality, this property is helpful to storage and transmission of data over internet.

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Index Terms

Computer Science
Information Sciences

Keywords

Peak signal noise ratio (PSNR) compression ratio (CR) mean square error (MSE) DWT threshold

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