Comparative Performance Evaluation of Three Image Compression Algorithms

  • 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.

References

Singh, Singh, A.K. and Tripathi, G.S. (2014). A Comparative Study of DCT, DWR and hybrid (DCTDWT) Transform, GJESER Review Paper, Vol. 1, No. 4, pp. 16-21.

Dhawan, S. (2011). A Review of Image Compression and Comparison of its Algorithms, International Journal of Electronics and Communication Technology, Vol. 2, No. 1, pp. 22-26.

Gupta, B. (2013). Study of Various Lossless Image Compression Techniques, International Journal of Emergimg Trends and Technology in Computer Science, Vol. 2, No. 4, pp. 253-257.

Rehman, M., Sharif, M. and Raza, M. (2014). Image Compression: A Survey, Research Journal of Applied Sciences, Engineering and Technology, Vol. 7, No. 4, pp. 256-672.

https://doi.org/10.19026/rjaset.7.303

Nivedita, M. Singh, P., and Jindal, S. (2012). A Comparative Study of DCT And DWT-SPIHT. International Journal of Computational Engineering and Management, Vol. 15, No. 2, pp. 26-32.

Pensiri, F. and Auwatanamongkol, S. (2012). A Lossless Image Compression Algorithm Using Predictive Coding Based on Quantized Colors, WSEAS Transactions on Signal Processing, Vol. 8, No. 2, pp. 43-53.

Alarabeyyat, A., Al-Hashemi S., Khdour, T., Btoush, M.H., Bani-Ahmad, S. and Al-Hashemi, R. (2012), Lossless Image Compression Technique Using Combination Methods, Journal of Software Engineering and Applications, Vol. 5, pp. 752-763.

https://doi.org/10.4236/jsea.2012.510088

Weinberger, M.J., Seroussi, G. and Sapiro, G. (2000). The LOCO-I Lossless Image Compression Algorithm: Principles and Standardization into JPEG-LS, IEEE Trans. on Image Processing, Vol. 9, No. 8, pp. 1309-1324.

https://doi.org/10.1109/83.855427

Zuo, Z., Lan, X., Deng, L., Yao, S. and Wang, X. (2015). An Improved Medical Image Compression Technique with Lossless Region of Interest. Optik-International Journal for Light and Electron Optics, Vol. 126, No. 21, pp. 2825-2831.

https://doi.org/10.1016/j.ijleo.2015.07.005

Tomar, R.R.S. and Jain, K. (2016). Lossless Image Compression Using Differential Pulse Code Modulation and its Application, International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol. 9, No. 1, pp. 197-202.

https://doi.org/10.14257/ijsip.2016.9.1.18

Masood, S., Sherif, M., Yasmin, M., Raza, M. and Mohsin, S. (2012). Brain Image Compression: A Brief Survey. Research Journal of Applied Sciences, Engineering and Technology, Vol. 5, No. 1, pp. 49-59.

https://doi.org/10.19026/rjaset.5.5083

Marimuthu, M., Muthaiah, R. and Swaminathan, P. (2012). Review Article: An Overview of Image Compression Techniques. Research Journal of Applied Sciences, Engineering and Technology, Vol. 4, No. 24, pp. 5381-5386.

Vijayvargiya, G., Silakari, S. and Pandy, R. (2013). A Survey: Various Techniques of Image Compression. International Journal of Computer and Information Security, Vol. 11, No. 10, pp. 51-55.

Rehna, V.J.and Jeya Kumar, M.K. (2012). Wavelet Based Image Coding Schemes: A Recent Survey, International Journal of Soft Computing, Vol. 3, No. 3, pp. 101-118.

https://doi.org/10.5121/ijsc.2012.3308

Wallace, G.K. (1991). The JPEG Still Picture Compression Standard, Communications of the ACM Magazine, Vol. 34, No. 4, pp. 30-44.

https://doi.org/10.1145/103085.103089

Puri, A. (1992). Video Coding Using the MPEG-1 Compression Standard, Society for Information Display Digest of Technical Papers, Vol. 23, pp. 123-126.

Watson, A.B. (1994). Image Compression Using the Discrete Cosine Transform, Mathematica Journal, Vol. 4, No. 1, pp. 81-88.

Yadavi, R.J., Gangwar, S.P. and Singh, H.V. (2012). Study and Analysis of Wavelet Based Image Compression Techniques International Journal of Engineering, Science and Technology, Vol. 4, No. 1, pp. 1-7.

https://doi.org/10.4314/ijest.v4i1.1S

Bindu, K., Ganpati, A. and Sharma, A.K. (2012). A Comparative Study of Image Compression Algorithms, International Journal of Research in Computer Science, Vol. 2, No. 5, pp. 37-42.

https://doi.org/10.7815/ijorcs.25.2012.046

Deshlahral, A., Shirnewar, G.S. and Sahoo, A.K. (2013). A Comparative Study of DCT, DWT and Hybrid (DCT-DWT) Transform, In Proceedings International Conference on Emerging Trends in Computer and Image Processing, February 24, pp. 1-7.

Al-Janabi, A.K. (2013). Low Memory Set-Partitioning in Hierarchical Trees Image Compression Algorithm, International Journal of Video and Image Processing and Network Security, Vol. 13, No. 2, pp. 12-18.

Rema, N.R., Binu A.O. and Mythili, P. (2015). Image Compression Using SPIHT with Modified Spatial Orientation Tress, Procedia Computer Science, Vol. 46, pp. 1732-1738.

https://doi.org/10.1016/j.procs.2015.02.121

Chowdhury, M.M.H. and Khatun, A. (2012). Image Compression Using Discrete Wavelet Transform, International Journal of Computer Science Issues, Vol. 9, No. 1, pp. 327-330.

Saffor, A., Ramli, A R. and Ng, K-H. (2001). A Comparative Study of Image Compression between JPEG and WAVELET, Malaysian Journal of Computer Science, Vol. 14, No. 1, pp. 39-45.

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 & 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

Copyright (c) 2017 Journal of Applied Science & Process Engineering

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright Transfer Statement for Journal

1) In signing this statement, the author(s) grant UNIMAS Publisher an exclusive license to publish their original research papers. The author(s) also grant UNIMAS Publisher permission to reproduce, recreate, translate, extract or summarize, and to distribute and display in any forms, formats, and media. The author(s) can reuse their papers in their future printed work without first requiring permission from UNIMAS Publisher, provided that the author(s) acknowledge and reference publication in the Journal.

2) For open access articles, the author(s) agree that their articles published under UNIMAS Publisher are distributed under the terms of the CC-BY-NC-SA (Creative Commons Attribution-Non Commercial-Share Alike 4.0 International License) which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original work of the author(s) is properly cited.

3) For subscription articles, the author(s) agree that UNIMAS Publisher holds copyright, or an exclusive license to publish. Readers or users may view, download, print, and copy the content, for academic purposes, subject to the following conditions of use: (a) any reuse of materials is subject to permission from UNIMAS Publisher; (b) archived materials may only be used for academic research; (c) archived materials may not be used for commercial purposes, which include but not limited to monetary compensation by means of sale, resale, license, transfer of copyright, loan, etc.; and (d) archived materials may not be re-published in any part, either in print or online.

4) The author(s) is/are responsible to ensure his or her or their submitted work is original and does not infringe any existing copyright, trademark, patent, statutory right, or propriety right of others. Corresponding author(s) has (have) obtained permission from all co-authors prior to submission to the journal. Upon submission of the manuscript, the author(s) agree that no similar work has been or will be submitted or published elsewhere in any language. If submitted manuscript includes materials from others, the authors have obtained the permission from the copyright owners.

5) In signing this statement, the author(s) declare(s) that the researches in which they have conducted are in compliance with the current laws of the respective country and UNIMAS Journal Publication Ethics Policy. Any experimentation or research involving human or the use of animal samples must obtain approval from Human or Animal Ethics Committee in their respective institutions. The author(s) agree and understand that UNIMAS Publisher is not responsible for any compensational claims or failure caused by the author(s) in fulfilling the above-mentioned requirements. The author(s) must accept the responsibility for releasing their materials upon request by Chief Editor or UNIMAS Publisher.

6) The author(s) should have participated sufficiently in the work and ensured the appropriateness of the content of the article. The author(s) should also agree that he or she has no commercial attachments (e.g. patent or license arrangement, equity interest, consultancies, etc.) that might pose any conflict of interest with the submitted manuscript. The author(s) also agree to make any relevant materials and data available upon request by the editor or UNIMAS Publisher.

To download Copyright Transfer Statement for Journal, click here