Review of Wavelet Theory and Its Application Toimage Data Compression

The fast development of computing multimedia has led to the demand of using digital images. The manipulation, storage and transmission of these images in their raw form is very expensive, it significantly slows the transmission and makes storage costly. In this paper, a brief review of wavelet trans...

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Main Author: Othman Omran Khalifa
Format: Article
Language:English
Published: IIUM Press, International Islamic University Malaysia 2012-10-01
Series:International Islamic University Malaysia Engineering Journal
Online Access:http://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/368
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spelling doaj-8d21f7f83c0c4ef0b5e0ddbbb27bfa452020-11-25T03:16:53ZengIIUM Press, International Islamic University MalaysiaInternational Islamic University Malaysia Engineering Journal1511-788X2289-78602012-10-014110.31436/iiumej.v4i1.368Review of Wavelet Theory and Its Application Toimage Data CompressionOthman Omran Khalifa0Electrical & Computer Department, Kulliyyah of Engineering, International Islamic University Malaysia, Jalan Gombak, 53100, Kuala Lumpur, Malaysia Fax: +603 2056 4853,The fast development of computing multimedia has led to the demand of using digital images. The manipulation, storage and transmission of these images in their raw form is very expensive, it significantly slows the transmission and makes storage costly. In this paper, a brief review of wavelet transform theory is given using filters as examples to show the related multiresolution analysis. Advantages over Fourier transform is investigated and several results are derived. The pyramid algorithm is also presented and some features of wavelets in image data compression are given. A modified version of Lind Boze and Gray (LBG) algorithm using Partial Search Partial Distortion (PSPD) is presented for coding the wavelet coefficients to speed up the codebook generation and the search required for nearest neighbour codevector of input image. The proposed scheme can save 70 - 80 % of the Vector Quantization (VQ) encoding time as compared to fully search VQ and reduced arithmetic complexity with less sacrificing performance. Key Words: Image compression, Wavelets transform, Vector qQuantization http://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/368
collection DOAJ
language English
format Article
sources DOAJ
author Othman Omran Khalifa
spellingShingle Othman Omran Khalifa
Review of Wavelet Theory and Its Application Toimage Data Compression
International Islamic University Malaysia Engineering Journal
author_facet Othman Omran Khalifa
author_sort Othman Omran Khalifa
title Review of Wavelet Theory and Its Application Toimage Data Compression
title_short Review of Wavelet Theory and Its Application Toimage Data Compression
title_full Review of Wavelet Theory and Its Application Toimage Data Compression
title_fullStr Review of Wavelet Theory and Its Application Toimage Data Compression
title_full_unstemmed Review of Wavelet Theory and Its Application Toimage Data Compression
title_sort review of wavelet theory and its application toimage data compression
publisher IIUM Press, International Islamic University Malaysia
series International Islamic University Malaysia Engineering Journal
issn 1511-788X
2289-7860
publishDate 2012-10-01
description The fast development of computing multimedia has led to the demand of using digital images. The manipulation, storage and transmission of these images in their raw form is very expensive, it significantly slows the transmission and makes storage costly. In this paper, a brief review of wavelet transform theory is given using filters as examples to show the related multiresolution analysis. Advantages over Fourier transform is investigated and several results are derived. The pyramid algorithm is also presented and some features of wavelets in image data compression are given. A modified version of Lind Boze and Gray (LBG) algorithm using Partial Search Partial Distortion (PSPD) is presented for coding the wavelet coefficients to speed up the codebook generation and the search required for nearest neighbour codevector of input image. The proposed scheme can save 70 - 80 % of the Vector Quantization (VQ) encoding time as compared to fully search VQ and reduced arithmetic complexity with less sacrificing performance. Key Words: Image compression, Wavelets transform, Vector qQuantization
url http://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/368
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