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A review on sparse fast fourier transform applications in image processing

International Journal of Electrical and Computer Engineering (IJECE) 2020 26 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.

Hadhrami Ab Ghani, Hadhrami Ab Ghani, Mohamad Razwan Abdul Malek, Muhammad Fadzli Kamarul Azmi, Muhammad Fadzli Kamarul Azmi, Muhammad Jefri Muril, Muhammad Jefri Muril, Azızul Azizan Azızul Azizan

Summary

This review examined applications of sparse Fast Fourier Transform algorithms in image processing, covering use cases including lithography optimization, cancer detection, evolutionary arts, and wastewater treatment, arguing that the approach addresses computational limitations of conventional FFT for high-dimensional signals.

Fast Fourier Transform has long been established as an essential tool in signal processing. To address the computational issues while helping the analysis work for multi-dimensional signals in image processing, sparse Fast Fourier Transform model is reviewed here when applied in different applications such as lithography optimization, cancer detection, evolutionary arts and wasterwater treatment. As the demand for higher dimensional signals in various applications especially multimedia appplications, the need for sparse Fast Fourier Transform grows higher.

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