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An Application of Linear Algebra to Image Compression

  • Khalid EL AsnaouiEmail author
  • Mohamed Ouhda
  • Brahim Aksasse
  • Mohammed Ouanan
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 228)

Abstract

Nowadays the data are transmitted in the form of images, graphics, audio and video. These types of data require a lot of storage capacity and transmission bandwidth. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossy compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab’s SVD function. The quantitative and visual results are showing the superiority of the proposed compression method over those of Matlab’s SVD function and some different compression techniques in the state-of-the-art. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords

Image compression Singular value decomposition Block SVD Power Method Lossy image compression PSNR 

Notes

Acknowledgements

The authors would like to thank the anonymous reviewers for their insightful comments in improving the quality of this paper.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Khalid EL Asnaoui
    • 1
    Email author
  • Mohamed Ouhda
    • 1
  • Brahim Aksasse
    • 1
  • Mohammed Ouanan
    • 1
  1. 1.M2I Laboratory, Faculty of Sciences and Techniques, Department of Computer Science, ASIA TeamMoulay Ismail UniversityErrachidiaMorocco

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