3305

Fast and accurate PIV computation using highly parallel iterative correlation maximization

F. Champagnat, A. Plyer, G. Le Besnerais, B. Leclaire, S. Davoust, Y. Le Sant
Information Processing and Modelling Department, French Aerospace Lab (ONERA), 29 avenue de la Division Leclerc, 92322, Chatillon Cedex, France
Experiments in Fluids (16 March 2011), pp. 1-14.

@article{springerlink:10.1007/s00348-011-1054-x,

   author={Champagnat, F. and Plyer, A. and Le Besnerais, G. and Leclaire, B. and Davoust, S. and Le Sant, Y.},

   affiliation={Modeling and Information Processing Department, French Aerospace Lab (ONERA), Chemin de la Huniere, 91761 Palaiseau Cedex, France},

   title={Fast and accurate PIV computation using highly parallel iterative correlation maximization},

   journal={Experiments in Fluids},

   publisher={Springer Berlin / Heidelberg},

   issn={0723-4864},

   keyword={Physics and Astronomy},

   pages={1-14},

   url={http://dx.doi.org/10.1007/s00348-011-1054-x},

   note={10.1007/s00348-011-1054-x},

   year={2011}

}

Download Download (PDF)   View View   Source Source   Source codes Source codes

Package:

656

views

Our contribution deals with fast computation of dense two-component (2C) PIV vector fields using Graphics Processing Units (GPUs). We show that iterative gradient-based cross-correlation optimization is an accurate and efficient alternative to multi-pass processing with FFT-based cross-correlation. Density is meant here from the sampling point of view (we obtain one vector per pixel), since the presented algorithm, folki, naturally performs fast correlation optimization over interrogation windows with maximal overlap. The processing of 5 image pairs (1,376 x
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: