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MEDICAL IMAGE COMPRESSION USING HYBRID METHOD OF SINGULAR VALUE DECOMPOSITION (SVD) AND DISCRETE WAVELET TRANSFORM (DWT) TO INCREASE ITS EFICIENCY OF SAVING AND TRANSMITION

This study aim was to increase the compression ratio and find out how much memory could be saved but also maintaining the quality of the image. The study was quantitative-analytic used samples of simple random sampling. Singular Value Decomposition algorithm (SVD) is a mathematical method to deciphe... Full description

Journal Title: LINK 01 February 2017, Vol.12(2), pp.72-77
Main Author: Subinarto Subinarto
Other Authors: Edy Susanto , Nina Indriyawati
Format: Electronic Article Electronic Article
Language: ind
Subjects:
Quelle: Directory of Open Access Journals (DOAJ)
ID: ISSN: 1829-5754 ; E-ISSN: 2461-1077 ; DOI: 10.31983/link.v12i2.1386
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recordid: doaj_soai_doaj_org_article_80f3488b455a47569d4d69ec740e0795
title: MEDICAL IMAGE COMPRESSION USING HYBRID METHOD OF SINGULAR VALUE DECOMPOSITION (SVD) AND DISCRETE WAVELET TRANSFORM (DWT) TO INCREASE ITS EFICIENCY OF SAVING AND TRANSMITION
format: Article
creator:
  • Subinarto Subinarto
  • Edy Susanto
  • Nina Indriyawati
subjects:
  • Medical Images
  • Lossy Compression
  • Singular Value Decomposition (Svd)
  • Discrete Wavelet Transform (Dwt)
ispartof: LINK, 01 February 2017, Vol.12(2), pp.72-77
description: This study aim was to increase the compression ratio and find out how much memory could be saved but also maintaining the quality of the image. The study was quantitative-analytic used samples of simple random sampling. Singular Value Decomposition algorithm (SVD) is a mathematical method to decipher a single matrix by compressing into three smaller matrices of the same size by reducing the data in columns and rows. while Discrete Wavelet Transform (DWT) is excellent in image energy concentrated on a small group of coefficients. It could also provide a combination of information about the frequency and scale resulting in a more accurate image reconstruction. Incorporation of these methods a compression system was lossy compression. The results of the compression process were carried out by compression rate calculation and MSSIM. The results of the study showed that compression system using a combination of SVD –DWT had a good performance. At Threshold_T = 15 and rank criteria _K = 4 generated the compression rate of 15.04% - 39.67%, or an average = 29.35% and MSSIM between 0.99 51,847 to 0.99 94 172 or average = 0.996219 with status almost close to 1, which mean the image of the original image compression and it could not be distinguished visual, it saved memory about 29.81%. It was better than DWT method tested in the same case with the result of the compression rate 28.85%.
language: ind
source: Directory of Open Access Journals (DOAJ)
identifier: ISSN: 1829-5754 ; E-ISSN: 2461-1077 ; DOI: 10.31983/link.v12i2.1386
fulltext: fulltext_linktorsrc
issn:
  • 1829-5754
  • 18295754
  • 2461-1077
  • 24611077
url: Link


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titleMEDICAL IMAGE COMPRESSION USING HYBRID METHOD OF SINGULAR VALUE DECOMPOSITION (SVD) AND DISCRETE WAVELET TRANSFORM (DWT) TO INCREASE ITS EFICIENCY OF SAVING AND TRANSMITION
creatorSubinarto Subinarto ; Edy Susanto ; Nina Indriyawati
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descriptionThis study aim was to increase the compression ratio and find out how much memory could be saved but also maintaining the quality of the image. The study was quantitative-analytic used samples of simple random sampling. Singular Value Decomposition algorithm (SVD) is a mathematical method to decipher a single matrix by compressing into three smaller matrices of the same size by reducing the data in columns and rows. while Discrete Wavelet Transform (DWT) is excellent in image energy concentrated on a small group of coefficients. It could also provide a combination of information about the frequency and scale resulting in a more accurate image reconstruction. Incorporation of these methods a compression system was lossy compression. The results of the compression process were carried out by compression rate calculation and MSSIM. The results of the study showed that compression system using a combination of SVD –DWT had a good performance. At Threshold_T = 15 and rank criteria _K = 4 generated the compression rate of 15.04% - 39.67%, or an average = 29.35% and MSSIM between 0.99 51,847 to 0.99 94 172 or average = 0.996219 with status almost close to 1, which mean the image of the original image compression and it could not be distinguished visual, it saved memory about 29.81%. It was better than DWT method tested in the same case with the result of the compression rate 28.85%.
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This study aim was to increase the compression ratio and find out how much memory could be saved but also maintaining the quality of the image. The study was quantitative-analytic used samples of simple random sampling. Singular Value Decomposition algorithm (SVD) is a mathematical method to decipher a single matrix by compressing into three smaller matrices of the same size by reducing the data in columns and rows. while Discrete Wavelet Transform (DWT) is excellent in image energy concentrated on a small group of coefficients. It could also provide a combination of information about the frequency and scale resulting in a more accurate image reconstruction. Incorporation of these methods a compression system was lossy compression. The results of the compression process were carried out by compression rate calculation and MSSIM. The results of the study showed that compression system using a combination of SVD –DWT had a good performance. At Threshold_T = 15 and rank criteria _K = 4 generated the compression rate of 15.04% - 39.67%, or an average = 29.35% and MSSIM between 0.99 51,847 to 0.99 94 172 or average = 0.996219 with status almost close to 1, which mean the image of the original image compression and it could not be distinguished visual, it saved memory about 29.81%. It was better than DWT method tested in the same case with the result of the compression rate 28.85%.

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This study aim was to increase the compression ratio and find out how much memory could be saved but also maintaining the quality of the image. The study was quantitative-analytic used samples of simple random sampling. Singular Value Decomposition algorithm (SVD) is a mathematical method to decipher a single matrix by compressing into three smaller matrices of the same size by reducing the data in columns and rows. while Discrete Wavelet Transform (DWT) is excellent in image energy concentrated on a small group of coefficients. It could also provide a combination of information about the frequency and scale resulting in a more accurate image reconstruction. Incorporation of these methods a compression system was lossy compression. The results of the compression process were carried out by compression rate calculation and MSSIM. The results of the study showed that compression system using a combination of SVD –DWT had a good performance. At Threshold_T = 15 and rank criteria _K = 4 generated the compression rate of 15.04% - 39.67%, or an average = 29.35% and MSSIM between 0.99 51,847 to 0.99 94 172 or average = 0.996219 with status almost close to 1, which mean the image of the original image compression and it could not be distinguished visual, it saved memory about 29.81%. It was better than DWT method tested in the same case with the result of the compression rate 28.85%.

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