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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Main Author: ABDUL KARIM, SAMSUL ARIFFIN
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.8883 /
Published: 2012
Subjects:
QA Mathematics
Online Access: http://eprints.utp.edu.my/8883/1/Final%20Paper.pdf
http://eprints.utp.edu.my/8883/
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recordtype eprints
spelling 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/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
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_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_ 1741196120536645632
score 11.62408

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