  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.
