Improved thresholding and quantization techniques for image compression

In recent decades, digital images have become increasingly important. With many modern applications use image graphics extensively, it tends to burden both the storage and transmission process. Despite the technological advances in storage and transmission, the demands placed on storage and bandwidt...

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Main Author:	Md Taujuddin, Nik Shahidah Afifi
Format:	Thesis
Language:	English English English
Published:	2017
Subjects:	TA1501-1820 Applied optics Photonics
Online Access:	http://eprints.uthm.edu.my/347/1/24p%20NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN.pdf http://eprints.uthm.edu.my/347/2/NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/347/3/NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN%20WATERMARK.pdf
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id	my-uthm-ep.347
record_format	uketd_dc
spelling	my-uthm-ep.3472021-07-22T07:40:47Z Improved thresholding and quantization techniques for image compression 2017-07 Md Taujuddin, Nik Shahidah Afifi TA1501-1820 Applied optics. Photonics In recent decades, digital images have become increasingly important. With many modern applications use image graphics extensively, it tends to burden both the storage and transmission process. Despite the technological advances in storage and transmission, the demands placed on storage and bandwidth capacities still exceeded its availability. Moreover, the compression process involves eliminating some data that degrades the image quality. Therefore, to overcome this problem, an improved thresholding and quantization techniques for image compression is proposed. Firstly, the generated wavelet coefficients obtained from the Discrete Wavelet Transform (DWT) process are thresholded by the proposed Standard Deviation-Based Wavelet Coefficients Threshold Estimation Algorithm. The proposed algorithm estimates the best threshold value at each detail subbands. This algorithm exploits the huge number of near-zero coefficients exist in detail subbands. For different images, the distribution of wavelet coefficients at each subband are substantially different. So, by calculating the standard deviation value of each subband, a better threshold value can be obtained. Next, the retained wavelet coefficients are subjected to the next proposed Minimizing Median Quantization Error Algorithm. The proposed algorithm utilizes the high occurrence of zero coefficient obtained by the previous thresholding process by re-allocating the zero and non-zero coefficients in different groups for quantization. Then, quantization error minimization mechanism is employed by calculating the median quantization error at each quantization interval class. The results are then compared to the existing algorithms and it is found that the proposed compression algorithm shows double increase in compression ratio performance, produces higher image quality with PSNR value above 40dB and ensures a better bit saving with smooth control at bit rate higher than 4 bpp. Thus, the proposed algorithm provides an alternative technique to compress the digital image. 2017-07 Thesis http://eprints.uthm.edu.my/347/ http://eprints.uthm.edu.my/347/1/24p%20NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN.pdf text en public http://eprints.uthm.edu.my/347/2/NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/347/3/NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Sains Komputer dan Teknologi Maklumat
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TA1501-1820 Applied optics Photonics
spellingShingle	TA1501-1820 Applied optics Photonics Md Taujuddin, Nik Shahidah Afifi Improved thresholding and quantization techniques for image compression
description	In recent decades, digital images have become increasingly important. With many modern applications use image graphics extensively, it tends to burden both the storage and transmission process. Despite the technological advances in storage and transmission, the demands placed on storage and bandwidth capacities still exceeded its availability. Moreover, the compression process involves eliminating some data that degrades the image quality. Therefore, to overcome this problem, an improved thresholding and quantization techniques for image compression is proposed. Firstly, the generated wavelet coefficients obtained from the Discrete Wavelet Transform (DWT) process are thresholded by the proposed Standard Deviation-Based Wavelet Coefficients Threshold Estimation Algorithm. The proposed algorithm estimates the best threshold value at each detail subbands. This algorithm exploits the huge number of near-zero coefficients exist in detail subbands. For different images, the distribution of wavelet coefficients at each subband are substantially different. So, by calculating the standard deviation value of each subband, a better threshold value can be obtained. Next, the retained wavelet coefficients are subjected to the next proposed Minimizing Median Quantization Error Algorithm. The proposed algorithm utilizes the high occurrence of zero coefficient obtained by the previous thresholding process by re-allocating the zero and non-zero coefficients in different groups for quantization. Then, quantization error minimization mechanism is employed by calculating the median quantization error at each quantization interval class. The results are then compared to the existing algorithms and it is found that the proposed compression algorithm shows double increase in compression ratio performance, produces higher image quality with PSNR value above 40dB and ensures a better bit saving with smooth control at bit rate higher than 4 bpp. Thus, the proposed algorithm provides an alternative technique to compress the digital image.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Md Taujuddin, Nik Shahidah Afifi
author_facet	Md Taujuddin, Nik Shahidah Afifi
author_sort	Md Taujuddin, Nik Shahidah Afifi
title	Improved thresholding and quantization techniques for image compression
title_short	Improved thresholding and quantization techniques for image compression
title_full	Improved thresholding and quantization techniques for image compression
title_fullStr	Improved thresholding and quantization techniques for image compression
title_full_unstemmed	Improved thresholding and quantization techniques for image compression
title_sort	improved thresholding and quantization techniques for image compression
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Sains Komputer dan Teknologi Maklumat
publishDate	2017
url	http://eprints.uthm.edu.my/347/1/24p%20NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN.pdf http://eprints.uthm.edu.my/347/2/NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/347/3/NIK%20SHAHIDAH%20AFIFI%20MD%20TAUJUDDIN%20WATERMARK.pdf
_version_	1747830588198354944

Improved thresholding and quantization techniques for image compression

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