Design and Simulation of a Low-Power and High-Speed Fast Fourier Transform for Medical Image Compression

• Published in: Engineering proceedings 2023-03, Vol.34 (1), p.18
• Main Authors: Ernest Ravindran Ramaswami Sachidanandan, Ngangbam Phalguni Singh, Sudhakiran Gunda
• Format: Article
• Language: English
• Subjects: discrete Fourier transform; fast Fourier transform; image compression; inverse discrete Fourier transform; inverse fast Fourier transform; radix-4
• ISSN: 2673-4591
• DOI: 10.3390/HMAM2-14159

For front-end wireless applications in small battery-powered devices, discrete Fourier transform (DFT) is a critical processing method for discrete time signals. Advanced radix structures are created to reduce the impact of transistor malfunction. To develop DFT, with radix sizes 4, 8, etc., is a complex and tricky issue for algorithm designers. The main reason for this is that the butterfly algorithm’s lower-radix-level equations were manually estimated. This requires the selection of a new design process. As a result of fewer calculations and smaller memory requirements for computationally intensive scientific applications, this research focuses on the radix-4 fast Fourier-transform (FFT) technique. A new 64-point DFT method based on radix-4 FFT and multi-stage strategy to solve DFT-related issues is presented in this paper. Based on the results of simulations with Xilinx ISE, it can be concluded that the algorithm developed is faster than conventional approaches, with an 18.963 ns delay and 12.68 mW of power consumption. It was found that the computed picture compression drop ratios of 0.10, 0.31, 0.61 and 0.83 had a direct relationship to the varied tolerances tested, 0.0007625, 0.003246, 0.013075 and 0.03924. Fast reconstruction techniques, wireless medical devices and other applications benefit from this FFT’s low power consumption, small storage requirements, and high processing speed.