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A Comparative Analysis of Various Image Compression Techniques

Authors: Udo EU, Odo KO, Ezeh C, Nwogu MO

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Digital images in their uncompressed form require extremely large amount of storage capacity that needs large transmission bandwidth for their transmission over networks. Image compression is one of the important parts of digital image processing because it reduces the data transmission time and data storage space. This paper investigated different image compression techniques used in reducing image size such as embedded zero tree wavelet (EZW), set partition in hierarchical tree (SPIHT) and discrete wavelet transform (DWT) for achieving better image compression in high compression ratio. MATLAB programs were written for each of these methods and the performance was evaluated in terms of peak signal to noise ratio (PSNR), mean square error (MSE) and compression ratio (CR). The results obtained show that the set partition in hierarchical tree with three dimensions (SPIHT_3D) technique produced the highest PSNR value of 43.6 dB and the lowest MSE value of 2.838. The embedded zero wavelet tree of level 5 produced the lowest PSNR value of 14.29 dB and the highest MSE value of 2423 while the discrete wavelet transform produced a low PSNR value of 26.91 dB and a low MSE value of 132.5. In conclusion, the SPIHT_3D technique produced the best image compression with better performance in high compression ratio compared to other existing image compression techniques.

Affiliations: Department of Electrical and Electronic Engineering, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria.
Keywords: Image Compression, Set Partition In Hierarchical Tree, Discrete Wavelet Transform, Embedded Zero Tree Wavelet, Digital Image Pro
Published date: 2022/06/30

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ISSN: 2635-3342 (Print)

ISSN: 2635-3350 (Online)

DOI: In progress

ISI Impact Factor: In progress

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Chemical Engineering Department, Faculty of Engineering, University of Benin, PMB 1154, Ugbowo, Benin City, Edo State, Nigeria.