Application of singular value decomposition in image processing

Rajesh A  Jadav and Shailesh S  Patel nbsp

doi:10.17485/ijst/2010/v3i2.2

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Application of singular value decomposition in image processing

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2010/v3i2.2

Year: 2010, Volume: 3, Issue: 2, Pages: 148-150

Original Article

Application of singular value decomposition in image processing

Rajesh A. Jadav and Shailesh S. Patel ^*

Dept. of Mathematics, S.V.M. Institute of Technology, College campus, Old N.H.-8, Bharuch-392001, Gujarat, India
[email protected] , [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

The purpose of this paper is to study an important application of Singular Value Decomposition (SVD) to image processing. The idea is that by using the smaller number of vectors, one can reconstruct an image that is closer to the original. The clarity of the image depends on how many singular values are used to reconstruct it. In this paper, SVD was applied to the image and also using the Matlab software we developed the code. We also demonstrated how the SVD is used to minimize the size needed to store an image.
Keywords: Singular value decomposition, image compression, image processing.