Indian Journal of Science and Technology

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Application of Singular Value Decomposition in Image Processing


Affiliations
1 Dept. of Mathematics, S.V.M. Institute of Technology, College campus, Old N.H.-8, Bharuch-392001, Gujarat, India
 

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
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  • Application of Singular Value Decomposition in Image Processing

Abstract Views: 781  |  PDF Views: 96

Authors

Rajesh A. Jadav
Dept. of Mathematics, S.V.M. Institute of Technology, College campus, Old N.H.-8, Bharuch-392001, Gujarat, India
Shailesh S. Patel
Dept. of Mathematics, S.V.M. Institute of Technology, College campus, Old N.H.-8, Bharuch-392001, Gujarat, India

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

References





DOI: https://doi.org/10.17485/ijst%2F2010%2Fv3i2%2F29667