1,721,012 research outputs found
Un software numerico per il riconoscimento e l’eliminazione dei blotch in sequenze di immagini digitali
No full textImage sequence inpainting: a numerical approach for blotch detection and removal via motion estimation
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Un software numerico basato sull’analisi in multirisoluzione per la stima del flusso ottico
No full textA GPU parallel optimised blockwise NLM algorithm in a distributed computing system
No full textRecently, advanced computing systems are widely adopted in order to intensively elaborate a huge amount of biomedical data in the e-health field. An interesting challenge is to perform real-time diagnosis by means of complex computational environments. In this paper, we suggest to deal the most computationally expensive processing steps of a distributed cloud e-health system by the use of graphics processing units (GPUs). In the case study of the magnetic resonance imaging (MRI), for improving the quality of denoising and helping the real-time diagnosis, we have implemented a GPU parallel algorithm based on the optimised blockwise non-local means (OB-NLM) method. Experimental results have shown a significant improvement of healthcare processing practice in terms of execution time
HPC computation issues of the incremental 3D variational data assimilation scheme in OceanVar software
No full textReconstruction of implicit curves and surfaces via RBF interpolation
No full textAbstract Representation of curves and surfaces is a basic topic in computer graphic and computer aided design (CAD). In this paper we focus on theoretical and practical issues in using radial basis functions (RBF) for reconstructing implicit curves and surfaces from point clouds. We study the conditioning of the problem and give some insight on how the problem parameters and the results have to be taken in order to achieve meaningful solutions and avoid artifacts. Moreover, a strategy for decreasing the conditioning of the problem is suggested and a general framework for preconditioning and solving the problem, even for large datasets, is also provided
A class of piecewise interpolating functions based on barycentric coordinates
No full textPiecewise interpolation methods, as spline or Hermite cubic interpolation
methods, define the interpolant function by means of polynomial pieces and ensure
that some regularity conditions are guaranteed at the break-points. In this work, we
propose a novel class of piecewise interpolating functions whose expression depends
on the barycentric coordinates and a suitable weight function. The underlying idea
is to specialize to the 1D settings some aspects of techniques widely used in multidimensional
interpolation, namely Shepard’s, barycentric and triangle-based blending
methods. We show the properties of convergence for the interpolating functions and
discuss how, in some cases, the properties of regularity that characterize the weight
function are reflected on the interpolant function. Numerical experiments, applied to
some case studies and real scenarios, show the benefit of our method compared to
other interpolant models
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