6449

Iterative optimization methods for efficient image restoration on multicore architectures

Roberto Cavicchioli, Andrea Prearo, Riccardo Zanella, Gaetano Zanghirati, Luca Zanni
Department of Pure and Applied Mathematics, University of Modena and Reggio Emilia, via Campi 213/B, 41100, Modena, Italy
University of Ferrara, Preprint n. 373, 2011

@article{cavicchioli2011iterative,

   title={Iterative optimization methods for efficient image restoration on multicore architectures},

   author={Cavicchioli, R. and Prearo, A. and Zanella, R. and Zanghirati, G. and Zanni, L.},

   year={2011}

}

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This paper explores effective algorithms for the solution of numerical nonlinear optimization problems in image restoration. The technology of modern acquisition techniques and devices most often returns data of increasing size, so we focus on the Scaled Gradient Projection algorithm, which is well suited to large-scale applications. We present its parallel implementations on different hardware, namely Tesla-series GPUs and cluster of last-generation multi-core CPUs. Algorithm and codes are tested against both 2D and 3D meaningful real-world problems.
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