Image Reconstruction Using Singular Value Decomposition
The singular value decomposition (SVD) is an effective toolto 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 Squa...
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2012
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my.utp.eprints.88832017-03-20T01:59:26Z Image Reconstruction Using Singular Value Decomposition ABDUL KARIM, SAMSUL ARIFFIN QA Mathematics The singular value decomposition (SVD) is an effective toolto 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, Q_k still have very close to the original image. 2012-12-20 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/8883/1/Final%20Paper.pdf ABDUL KARIM, SAMSUL ARIFFIN (2012) Image Reconstruction Using Singular Value Decomposition. In: SIMPOSIUM KEBANGSAAN SAINS MATEMATIK KE 20 (SKSM 20) AIP INDEX, 18-20 DEC 2012, IOI RESORT, PUTRAJAYA. (In Press) http://eprints.utp.edu.my/8883/ |
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Universiti Teknologi Petronas |
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UTP Resource Centre |
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Institutional Repository |
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Asia |
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Malaysia |
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Universiti Teknologi Petronas |
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UTP Institutional Repository |
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http://eprints.utp.edu.my/ |
| topic |
QA Mathematics |
| spellingShingle |
QA Mathematics ABDUL KARIM, SAMSUL ARIFFIN Image Reconstruction Using Singular Value Decomposition |
| description |
The singular value decomposition (SVD) is an effective toolto 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, Q_k still have very close to the original image. |
| format |
Conference or Workshop Item |
| author |
ABDUL KARIM, SAMSUL ARIFFIN |
| author_facet |
ABDUL KARIM, SAMSUL ARIFFIN |
| author_sort |
ABDUL KARIM, SAMSUL ARIFFIN |
| 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 |
| publishDate |
2012 |
| url |
http://eprints.utp.edu.my/8883/1/Final%20Paper.pdf http://eprints.utp.edu.my/8883/ |
| _version_ |
1738655690409377792 |
| score |
13.251813 |