Image Compression Using Principle Component Analysis

Authors

  • amel abbas
  • abbas arab
  • Jamila harbi

DOI:

https://doi.org/10.23851/mjs.v29i2.256

Keywords:

lossy compression, PCA, Eigenvalue, and Eigenvector.

Abstract

Principle component analysis produced reduction in dimension, therefore in our proposed method used PCA in image lossy compression and obtains the quality performance of reconstructed image. PSNR values increase when the number of PCA components is increased and CR, MSE, and other error parameters decreases when the number of components is increased.

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References

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Key Dates

Published

17-11-2018

Issue

Section

Original Article

How to Cite

[1]
amel abbas, abbas arab, and J. harbi, “Image Compression Using Principle Component Analysis”, Al-Mustansiriyah Journal of Science, vol. 29, no. 2, pp. 141–147, Nov. 2018, doi: 10.23851/mjs.v29i2.256.