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Image Noise Removal on Heterogeneous CPU-GPU Configurations

Maria G. Sanchez, Vicente Vidal, Josep Arnal, Anna Vidal
Dpto. de Sistemas y Computacion, Instituto Tecnologico de Cd. Guzman, Cd. Guzman, Mexico
Procedia Computer Science, Volume 29, Pages 2219-2229, 2014

@article{Sanchez20142219,

   title={Image Noise Removal on Heterogeneous CPU-GPU Configurations},

   journal={Procedia Computer Science},

   volume={29},

   number={0},

   pages={2219 – 2229},

   year={2014},

   note={2014 International Conference on Computational Science},

   issn={1877-0509},

   doi={http://dx.doi.org/10.1016/j.procs.2014.05.207},

   url={http://www.sciencedirect.com/science/article/pii/S1877050914003846},

   author={Maria G. Sanchez and Vicente Vidal and Josep Arnal and Anna Vidal},

   keywords={OpenMP}

}

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A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.
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