Research on the fast Fourier transform of image based on GPU

TL;DR

This paper explores implementing a 2D FFT on GPU to enhance image processing speed, demonstrating significant performance gains over CPU especially with large images, and generalizing the approach to similar transforms.

Contribution

It introduces GPU-based parallelization of the radix-2 FFT algorithm, including kernel design and implementation for 2D FFT, showing improved efficiency over traditional CPU methods.

Findings

GPU implementation outperforms CPU in large input scenarios

Designed efficient butterfly and scramble kernels for GPU

Approach can be generalized to other similar transforms

Abstract

Study of general purpose computation by GPU (Graphics Processing Unit) can improve the image processing capability of micro-computer system. This paper studies the parallelism of the different stages of decimation in time radix 2 FFT algorithm, designs the butterfly and scramble kernels and implements 2D FFT on GPU. The experiment result demonstrates the validity and advantage over general CPU, especially in the condition of large input size. The approach can also be generalized to other transforms alike.