Fast and accurate PIV computation using highly parallel iterative correlation maximization
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.
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
March 22, 2011 by hgpu
Your response
You must be logged in to post a comment.