Image reconstruction using singular value decomposition
The singular value decomposition (SVD) is an effective tool to reconstruct the image approximately towards the original image. This paper will introduce and explores image reconstruction by applying the SVD on gray-scale image. As quality measurements, we used Compression Ratio (CR) and Root-Mean Sq...
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AIP Publishing
2013
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my.ums.eprints.185932018-02-03T13:52:35Z https://eprints.ums.edu.my/id/eprint/18593/ Image reconstruction using singular value decomposition Samsul Ariffin Abdul Karim Muhammad Izzatullah Mohd Mustafa Bakri Abdul Karim Mohammad Khatim Hasan Jumat Sulaiman Mohd Tahir Ismail TA Engineering (General). Civil engineering (General) The singular value decomposition (SVD) is an effective tool to reconstruct the image approximately towards the original image. This paper will introduce and explores image reconstruction by applying the SVD on gray-scale image. As quality measurements, we used Compression Ratio (CR) and Root-Mean Squared Error (RMSE). The results indicated that for certain images the value of k is smaller than for other images. The value of k is defined as the rank for the closet matrix and the constant integer k can be chosen expectantly less than diagonal matrix n, and the digital image corresponding to outer product expansion, Qk still have very close to the original image. AIP Publishing 2013-04 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/18593/1/Image%20reconstruction.pdf Samsul Ariffin Abdul Karim and Muhammad Izzatullah Mohd Mustafa and Bakri Abdul Karim and Mohammad Khatim Hasan and Jumat Sulaiman and Mohd Tahir Ismail (2013) Image reconstruction using singular value decomposition. AIP Conference Proceedings, 152 (1). pp. 269-274. ISSN 0094-243X https://doi.org/10.1063/1.4801133 |
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TA Engineering (General). Civil engineering (General) Samsul Ariffin Abdul Karim Muhammad Izzatullah Mohd Mustafa Bakri Abdul Karim Mohammad Khatim Hasan Jumat Sulaiman Mohd Tahir Ismail Image reconstruction using singular value decomposition |
description |
The singular value decomposition (SVD) is an effective tool to reconstruct the image approximately towards the original image. This paper will introduce and explores image reconstruction by applying the SVD on gray-scale image. As quality measurements, we used Compression Ratio (CR) and Root-Mean Squared Error (RMSE). The results indicated that for certain images the value of k is smaller than for other images. The value of k is defined as the rank for the closet matrix and the constant integer k can be chosen expectantly less than diagonal matrix n, and the digital image corresponding to outer product expansion, Qk still have very close to the original image. |
format |
Article |
author |
Samsul Ariffin Abdul Karim Muhammad Izzatullah Mohd Mustafa Bakri Abdul Karim Mohammad Khatim Hasan Jumat Sulaiman Mohd Tahir Ismail |
author_facet |
Samsul Ariffin Abdul Karim Muhammad Izzatullah Mohd Mustafa Bakri Abdul Karim Mohammad Khatim Hasan Jumat Sulaiman Mohd Tahir Ismail |
author_sort |
Samsul Ariffin Abdul Karim |
title |
Image reconstruction using singular value decomposition |
title_short |
Image reconstruction using singular value decomposition |
title_full |
Image reconstruction using singular value decomposition |
title_fullStr |
Image reconstruction using singular value decomposition |
title_full_unstemmed |
Image reconstruction using singular value decomposition |
title_sort |
image reconstruction using singular value decomposition |
publisher |
AIP Publishing |
publishDate |
2013 |
url |
https://eprints.ums.edu.my/id/eprint/18593/1/Image%20reconstruction.pdf https://eprints.ums.edu.my/id/eprint/18593/ https://doi.org/10.1063/1.4801133 |
_version_ |
1760229467003813888 |
score |
13.251813 |