Speeding-up image processing in reaction-diffusion cellular neural networks using CUDA-enabled GPU platforms

Due to their inherent architecture, the discrete time model of Cellular nonlinear networks (CNNs) for image processing are well suited candidates for efficient implementation using massively parallel architectures. This paper proposes an implementation model for GPU architectures and highlights the advantages over the CPU version, using nVidia's CUDA platform.