Iterative image deformation methods in PIV

By Fulvio Scarano. 2002

981 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition, Ecology

View Paper: https://www.semanticscholar.org/paper/07a22cb56e2649d0fc32bc4acc5940cafea02aaf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

In Computer Vision and Pattern Recognition

In Ecology

Citations in the corpus

Measurement of laminar, transitional and turbulent pipe flow using Stereoscopic-PIV (2007, background): “The relation between these control parameters and the measurement accuracy is subject of extensive research (Keane and Adrian 1993; Westerweel 2000a; Scarano 2002; Foucaut et al. 2004).”
The accuracy of tomographic particle image velocimetry for measurements of a turbulent boundary layer (2011, methodology): “One method of improving the precision of velocity estimates from PIV measurements involves the use of interrogation window or volume deformation (Huang et al. 1993; Scarano 2002 ), where a sub-pixel volume offset is applied to improve sub-pixel estimates of velocity.”
Importance of the nozzle-exit boundary-layer state in subsonic turbulent jets (2018, background): “Simulations of subsonic turbulent jets 35 local mean velocity gradients (Scarano 2002).”
Three-dimensional vorticity patterns of cylinder wakes (2009, methodology): “Between subsequent iterations low-pass filtering by 2nd order 3D least squares regression is applied to the velocity field for process stabilization (Schrijer and Scarano 2008). Fig. 4 Left reconstructed light intensity distribution averaged along the cylinder span. Right the average intensity profi”
Experimental characterization of the turbulent boundary layer over a porous trailing edge for noise abatement (2019, methodology): “A multi-pass cross-correlation algorithm [65] with window deformation [66] is applied to the sequence of images resulting in 10913 vector fields.”
Phase-resolved characterization of vortex shedding in the near wake of a square-section cylinder at incidence (2005, methodology): “Image analysis was carried out with a window deformation and iterative multi-grid cross-correlation algorithm (WIDIM, Scarano 2002 ) using an interrogation window size of 40·40 pixels and an overlap factor of 75%, yielding a measurement grid with a spacing of 10 pixels (circa 1 mm or 0.03D).”
Experimental study of eddy structures in a turbulent boundary layer using particle image velocimetry (2005, methodology): “Such a bias can now be reduced by using a PIV algorithm with interrogation window deformation (see Scarano 2002) which was not available at the time of the experiments.”
Spectral proper orthogonal decomposition (2015, methodology): “t 1kHz). The PIV data were processed with PIVview (PIVTEC GmbH) using standard digital PIV processing (Willert & Gharib 1991) enhanced by iterative multigrid interrogation with image deformation (Scarano 2002),(Rael et al. 2007, pp. 146-158). Analyzing the present data sets with existing POD, DF”
PIV uncertainty quantification by image matching (2013, methodology): “The method based on discrete offset will match the particle motion within uniform (planar) velocity approximation; the image deformation method will match the particle motion up to a piecewise linear approximation (Scarano 2002, Astarita and Cardone 2005).”
On velocity gradients in PIV interrogation (2008, background): “If the gradient only occurs in the in-plane components of the displacement, then it is possible to (partially) compensate for the effects of the gradients in the displacement by means of local image deformation (Huang et al. 1993; Tokumaru and Dimotakis 1995; Fincham and Delerce 2000; Scarano 2002).”
Multi-frame pyramid correlation for time-resolved PIV (2012, methodology): “The pyramid correlation algorithm is based on the WIDIM interrogation algorithm (Scarano and Riethmuller 2000), which performs a progressive reduction of the interrogation windows along with the deformation of the particle images pattern that compensates for the in-plane particle image motion. Detai”