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Performance comparison of FPGA, GPU and CPU for an anisotropic diffusion filter

Amira Hadj Fredj, Jihene Malek


The anisotropic diffusion algorithm proposed by Perona and Malik has given remarkable denoising results. SRAD is the most suitable anisotropic diffusion technique, which allows good noise suppression while preserving the edges at an expensive cost of calculation. Recent computational platform developments and advances in machine vision has provided us with several options for anisotropic diffusion algorithm implementation. In order to exploit the shortest execution time for the anisotropic diffusion process, the SRAD method is implemented on three different platforms: a Central Processing Unit (CPU), a Graphics Processing Unit (GPU) and a Field-Programmable Gate Array (FPGA). Implementations are done in MATLAB, CUDA or C++ and VHDL programming languages. Designs for achievements on the FPGA, the GPU and the CPU are shown and the results of their performance analysed using a retinal image of size 128 x 128 are presented.


Anisotropic diffusion, SRAD filter, GPU, FPGA.

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