Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation

The objective of image compression is to reduce the number of bits required to represent an image. The art of developing and designing an image compression scheme is balancing among the compression ratio, distortion and the processing time. Existing compression techniques involve low and high compre...

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Main Author:	Alsayyh, Moh’Dali Moustafa
Format:	Thesis
Language:	English
Published:	2015
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/54696/1/Moh%E2%80%99DaliMoustafaAlsayyhPFC2015.pdf
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spelling	my-utm-ep.546962020-11-03T08:34:50Z Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation 2015-06 Alsayyh, Moh’Dali Moustafa QA75 Electronic computers. Computer science The objective of image compression is to reduce the number of bits required to represent an image. The art of developing and designing an image compression scheme is balancing among the compression ratio, distortion and the processing time. Existing compression techniques involve low and high compression ratio of significant loss of image quality. New image compressing technique is required for storage. In this thesis, a new technique is proposed to compress the image and to gain higher compression ratio with smaller distortion. The main features of the proposed hybrid image compression are high compression ratio and high resolution of decompressed images. The new technique is combining three different algorithms: Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT). The proposed technique uses features of these algorithms and it consists of three steps. In the first step, DFT was applied to compress image, in the second step, DWT was applied and in the third step DCT was applied to compress image. The experimental results show that the proposed hybrid image compression achieved high compression ratio while preserving the quality of the reconstructed image. The experimental results also show that the Peak Signal-to- Noise Ratio (PSNR) value of the proposed technique was 83.6914 and the Mean Square Error (MSE) value was 2.7793 for Lena image. For all standard images, the results show that the proposed hybrid image compression performed better than the existing methods in terms of PSNR and in terms of MSE values. Finally, the proposed hybrid image compression further improves the image transmission and storage capacity of the image. 2015-06 Thesis http://eprints.utm.my/id/eprint/54696/ http://eprints.utm.my/id/eprint/54696/1/Moh%E2%80%99DaliMoustafaAlsayyhPFC2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:94638 phd doctoral Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Alsayyh, Moh’Dali Moustafa Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation
description	The objective of image compression is to reduce the number of bits required to represent an image. The art of developing and designing an image compression scheme is balancing among the compression ratio, distortion and the processing time. Existing compression techniques involve low and high compression ratio of significant loss of image quality. New image compressing technique is required for storage. In this thesis, a new technique is proposed to compress the image and to gain higher compression ratio with smaller distortion. The main features of the proposed hybrid image compression are high compression ratio and high resolution of decompressed images. The new technique is combining three different algorithms: Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT). The proposed technique uses features of these algorithms and it consists of three steps. In the first step, DFT was applied to compress image, in the second step, DWT was applied and in the third step DCT was applied to compress image. The experimental results show that the proposed hybrid image compression achieved high compression ratio while preserving the quality of the reconstructed image. The experimental results also show that the Peak Signal-to- Noise Ratio (PSNR) value of the proposed technique was 83.6914 and the Mean Square Error (MSE) value was 2.7793 for Lena image. For all standard images, the results show that the proposed hybrid image compression performed better than the existing methods in terms of PSNR and in terms of MSE values. Finally, the proposed hybrid image compression further improves the image transmission and storage capacity of the image.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Alsayyh, Moh’Dali Moustafa
author_facet	Alsayyh, Moh’Dali Moustafa
author_sort	Alsayyh, Moh’Dali Moustafa
title	Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation
title_short	Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation
title_full	Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation
title_fullStr	Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation
title_full_unstemmed	Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation
title_sort	improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2015
url	http://eprints.utm.my/id/eprint/54696/1/Moh%E2%80%99DaliMoustafaAlsayyhPFC2015.pdf
_version_	1747817705092677632

Improved image compression scheme using hybrid of discrete fourier, wavelets and cosine transformation

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