Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Jadav, Rajesh A.
- Application of Singular Value Decomposition in Image Processing
Abstract Views :771 |
PDF Views:96
Authors
Affiliations
1 Dept. of Mathematics, S.V.M. Institute of Technology, College campus, Old N.H.-8, Bharuch-392001, Gujarat, IN
1 Dept. of Mathematics, S.V.M. Institute of Technology, College campus, Old N.H.-8, Bharuch-392001, Gujarat, IN
Source
Indian Journal of Science and Technology, Vol 3, No 2 (2010), Pagination: 148-150Abstract
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 ProcessingReferences
- Bakwad KM, Pattnaik SS, Sohil BS, Panigrahi BK, Sastry VRS and Gollapudi (2009) Bacterial foraging optimization technique cascaded with adaptive filter to enhance peak signal to noise ratio from signal image. IETE J. Res. 55(4), 173-179.
- Jain AK (2004) Fundamental of digital image processing. Pearson Edu. India. p: 176-180.
- Jain SK and Gunawardena AD (2003) Linear Algebra: An Interactive Approach. Thomson Asia Pvt. Ltd. pp: 216-220.
- Jody S. Hourigan and Lynn V. McIndoo (1998) Singular value decomposition. Lin. Algebra-Maths-45, College of Redwoods.
- Ogden CJ and Huff T (1997) The singular value decomposition and its application in image processing. Lin. Algebra-Maths- 45, College of Redwoods.