Image Compression Techniques Using Linear Algebra with SVD Algorithm

Authors

  • S. Karthigai Selvam Assistant Professor, Department of Mathematics, N.M.S.S.V.N. College, Madurai, Tamil Nadu, India
  • S. Selvam Head and Assistant Professor, Department of Computer Applications, N.M.S.S.V.N. College, Madurai, Tamil Nadu, India

DOI:

https://doi.org/10.51983/ajeat-2021.10.1.2724

Keywords:

Image Compression, Singular Value Decomposition, MSE, Lossy Image Compression, PSNR

Abstract

In recent days, the data are transformed in the form of multimedia data such as images, graphics, audio and video. Multimedia data require a huge amount of storage capacity and transmission bandwidth. Consequently, data compression is used for reducing the data redundancy and serves more storage of data. In this paper, addresses the problem (demerits) of the lossy compression of images. This proposed method is deals on SVD Power Method that overcomes the demerits of Python SVD function. In our experimental result shows superiority of proposed compression method over those of Python SVD function and some various compression techniques. In addition, the proposed method also provides different degrees of error flexibility, which give minimum of execution of time and a better image compression.

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Published

05-05-2021

How to Cite

Karthigai Selvam, S., & Selvam, S. (2021). Image Compression Techniques Using Linear Algebra with SVD Algorithm. Asian Journal of Engineering and Applied Technology, 10(1), 22–28. https://doi.org/10.51983/ajeat-2021.10.1.2724