Performance comparison of FPGA, GPU and CPU for an anisotropic diffusion filter
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.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.