2D Discrete Fourier Transform with Simultaneous Edge Artifact Removal for Real-Time Applications

TL;DR

This paper introduces an FPGA-based 2D DFT method that efficiently removes edge artifacts in real-time, enhancing image processing accuracy without increasing computational load or memory conflicts.

Contribution

A novel FPGA implementation of 2D DFT with integrated edge artifact removal using periodic-plus-smooth decomposition, optimized for high throughput and reduced memory usage.

Findings

Achieves real-time processing of 512x512 images at ≥23 fps.

Effectively removes edge artifacts without increasing computation or memory conflicts.

Demonstrates suitability for industrial applications with FPGA hardware.

Abstract

Two-Dimensional (2D) Discrete Fourier Transform (DFT) is a basic and computationally intensive algorithm, with a vast variety of applications. 2D images are, in general, non-periodic, but are assumed to be periodic while calculating their DFTs. This leads to cross-shaped artifacts in the frequency domain due to spectral leakage. These artifacts can have critical consequences if the DFTs are being used for further processing. In this paper we present a novel FPGA-based design to calculate high-throughput 2D DFTs with simultaneous edge artifact removal. Standard approaches for removing these artifacts using apodization functions or mirroring, either involve removing critical frequencies or a surge in computation by increasing image size. We use a periodic-plus-smooth decomposition based artifact removal algorithm optimized for FPGA implementation, while still achieving real-time ($\ge$23 frames per second) performance for a 512$\times$512 size image stream. Our optimization approach leads to a significant decrease in external memory utilization thereby avoiding memory conflicts and simplifies the design. We have tested our design on a PXIe based Xilinx Kintex 7 FPGA system communicating with a host PC which gives us the advantage to further expand the design for industrial applications.