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A comparison of application of Fourier Transform and Wavelet Transform on image compression
- 1 University of Wisconsin-Madison
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Abstract
This paper explores the application of Fourier Transform and Wavelet Transform in image compression, comparing their performance in terms of various parameters. As data compression continues to evolve to minimize storage and transmission costs, image compression techniques play a crucial role. Among the major compression methods, Fourier Transform and Wavelet Transform stand out. In this study, we introduce both transforms, elucidate their respective image compression methodologies, and undertake a comparative analysis of their compression qualities using multiple metrics. The mathematical underpinning of both transforms is discussed, and several quality metrics will serve as standards for comparison. In comparing the two techniques, Wavelet Transform consistently demonstrates better image compression quality, albeit with higher computational complexity. This study underscores the potential for further algorithmic enhancements to improve Fourier Transform-based compression and encourages an understanding of the trade-offs between compression quality and processing efficiency in the context of image compression techniques.
Keywords
Fourier transform, wavelet transform, image compression
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Cite this article
Kan,Y. (2024). A comparison of application of Fourier Transform and Wavelet Transform on image compression. Applied and Computational Engineering,37,149-154.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation
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