Comparative Performance Evaluation of Three Image Compression Algorithms

Authors

  • Jide Julius Popoola Department of Electrical and Electronics Engineering, School of Engineering and Engineering Technology, Federal University of Technology, Akure, Nigeria
  • Michael Elijah Adekanye Department of Electrical and Electronics Engineering, School of Engineering and Engineering Technology, Federal University of Technology, Akure, Nigeria

DOI:

https://doi.org/10.33736/jaspe.371.2017

Keywords:

Image compression, image, image compression methods, performance indices.

Abstract

The advent of computer and internet has brought about massive change to the ways images are being managed. This revolution has resulted in changes in image processing and management as well as the huge space requirement for images’ uploading, downloading, transferring and storing nowadays. In guiding against this huge space requirement, images need to be compressed before either storing or transmitting. Several algorithms or techniques on image compression had been developed in literature. In this study, three of these image compression algorithms were developed using MATLAB codes. The three algorithms developed are discrete cosine transform (DCT), discrete wavelet transform (DWT) and set partitioning in hierarchical tree (SPIHT). In order to ascertain which of them is most appropriate for image storing and transmission, comparative performance evaluations were conducted on the three developed algorithms using five performance indices. The results of the comparative performance evaluations show that the three algorithms are effective in image compression but with different efficiency rates. In addition, the comparative performance evaluations results show that DWT has the highest compression ratio and distortion level while the corresponding values for SPIHT is the lowest with those of DCT fall in-between. Also, the results of the study show that the lower the mean square error and the higher the peak signal-to-noise-ratio, the lower the distortion level in the compressed image.

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Published

2017-04-28

How to Cite

Popoola, J. J., & Adekanye, M. E. (2017). Comparative Performance Evaluation of Three Image Compression Algorithms. Journal of Applied Science &Amp; Process Engineering, 4(1), 113–126. https://doi.org/10.33736/jaspe.371.2017

Issue

Vol. 4 No. 1 (2017): Journal of Applied Science & Process Engineering, Volume 4, Number 1, 2017

Section

Articles

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