Image Reconstruction Using Singular Value Decomposition

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)

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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.

Item Type:Conference or Workshop Item (Paper)
Subjects:Q Science > QA Mathematics
Academic Subject One:MATHEMATICS
Academic Subject Two:Geoscience
Academic Subject Three:petroleum engineering
Departments / MOR / COE:Departments > Fundamental & Applied Sciences
Research Institutes > Energy
ID Code:8883
Deposited By: Samsul Ariffin Abdul Karim
Deposited On:31 Jan 2013 23:53
Last Modified:20 Mar 2017 01:59

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