Skip to main content
Log in

Analysis of interpolation schemes for image deformation methods in PIV: effect of noise on the accuracy and spatial resolution

  • Research Article
  • Published:
Experiments in Fluids Aims and scope Submit manuscript

Abstract

As testified by a previous article (Astarita and Cardone in Exp Fluids 38:233–243, 2005), a critical point that can influence significantly the accuracy of image deformation methods (IDM) for particle image velocimetry (PIV) is the interpolation scheme (IS) used in the reconstruction of deformed images. In the cited paper the effect of noise has been neglected and for this reason in this follow-up paper the influence of the IS, in the presence of noise, on both accuracy and spatial resolution is studied. Performance assessment is conducted using synthetic images with particles of Gaussian shape and with constant and sinusoidal displacement fields. Both the local and the top hat moving average approaches are investigated and the modulation transfer function, the total and bias errors have been used to evaluate the performances of IDMs for PIV applications. The results show that, when a high noise level is present in the images, the influence of the IS is less relevant than what was shown by Astarita and Cardone (Exp Fluids 38:233–243, 2005).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Abbreviations

BSPLM :

Interpolation scheme based on the B-spline of order M

FFT:

Fast Fourier transform

IDM:

Image deformation method

IDWO:

Iterative discrete window offset

IS:

Interpolation scheme

MTF:

Modulation transfer function

PIV:

Particle image velocimetry

THMA:

Top hat moving average

a :

modulation factor associated to the predictor displacement field, dimensionless

a k :

modulation factor at iteration k, dimensionless

b :

modulation factor associated with steps 2 and 5 of the algorithm, dimensionless

D :

particle diameter, pixels

f :

grey intensity of the first image, dimensionless

g :

grey intensity of the second image, dimensionless

i :

horizontal image coordinate (integer value), pixels

j :

vertical image coordinate (integer value), pixels

k :

iteration number, dimensionless

l :

horizontal shift, pixels

m :

vertical shift, pixels

n :

random noise level, dimensionless

N :

number of measurement points, dimensionless

p :

percentage of lost particles, dimensionless

r :

displacement field, pixels

r c :

corrector displacement field, pixels

r i :

interpolated predictor displacement field, pixels

r w :

displacement field averaged over the interrogation window, pixels

\(\ifmmode\expandafter\bar\else\expandafter\=\fi{u}\) :

mean measured displacement, pixels

u :

imposed displacement, pixels

u i :

local measured displacement, pixels

U :

amplitude of the sinusoidal displacement field, pixels

w :

weighting function, dimensionless

W :

interrogation window linear dimension, pixels

x :

horizontal image coordinate, pixels

y :

vertical image coordinate, pixels

β :

bias error, pixels

\(\ifmmode\expandafter\bar\else\expandafter\=\fi{\delta }\) :

mean total error, pixels

δ :

total error, pixels

δ n :

total error associated to a random noise equal to n, pixels

δ e n :

estimated total error associated to a random noise equal to n, pixels

λ :

spatial wavelength, pixels

μ :

mean operator

φ lm :

cross-correlation coefficient, dimensionless

ω :

normalised spatial frequency (W/λ), dimensionless

Reference

  • Astarita T, Cardone G (2005) Analysis of interpolation schemes for image deformation methods in PIV. Exp Fluids 38:233–243

    Article  Google Scholar 

  • Cowen EA, Monismith SG (1997) A hybrid digital particle tracking velocimetry technique. Exp Fluids 22:199–211

    Article  Google Scholar 

  • Gui L, Wereley ST (2002) A correlation-based continuous window-shift technique to reduce the peak-locking effect in digital PIV image evaluation. Exp Fluids 32:506–517

    Article  Google Scholar 

  • Huang HT, Fiedler HE, Wang JJ (1993) Limitation and improvement of PIV. 2. Particle image distortion, a novel technique. Exp Fluids 15:263–273

    Google Scholar 

  • Jambunathan K, Ju XY, Dobbins BN, Ashforth-Frost S (1995) An improved cross correlation technique for particle image velocimetry. Meas Sci Technol 6:507–514

    Article  Google Scholar 

  • Keane RD, Adrian RJ (1993) Theory of cross correlation analysis of PIV images. In: Nieuwstadt FTM (ed) Flow visualization and image analysis. Kluwer, Dordrecht, pp 1–25

  • Lecordier B, Demare D, Vervisch LMJ, Rèveillon J, Trinitè M (2001) Estimation of the accuracy of PIV treatments for turbulent flow studies by direct numerical simulation of multi-phase flow. Meas Sci Technol 12:1382–1391

    Article  Google Scholar 

  • Lecuona A, Nogueira J, Rodriguez PA, Santana D (2002) Accuracy and time performance of different schemes of the local field correction PIV technique. Exp Fluids 33:743–751

    Google Scholar 

  • Liao Q, Cowen EA (2005) An efficient anti-aliasing spectral continuous window shifting technique for PIV. Exp Fluids 38:197–208

    Article  Google Scholar 

  • Meunier P, Leweke T (2003) Analysis and treatment of errors due to high velocity gradients in particle image velocimetry. Exp Fluids 35:408–421

    Article  Google Scholar 

  • Nogueira J, Lecuona A, Rodriguez PA (1999) Local field correction PIV: on the increase of accuracy of digital PIV systems. Exp Fluids 27:107–116

    Article  Google Scholar 

  • Nogueira J, Lecuona A, Rodriguez PA (2001) Local field correction PIV, implemented by means of simple algorithms, and multigrid versions. Meas Sci Technol 12:1911–1921

    Article  Google Scholar 

  • Raffel M, Willert CE, Kompenhans J (1998) Particle image velocimetry: a practical guide. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Scarano F (2004) A super-resolution particle image velocimetry interrogation approach by means of velocity second derivatives correlation. Meas Sci Technol 15:475–486

    Article  Google Scholar 

  • Scarano F, Riethmuller ML (1999) Iterative multigrid approach in PIV image processing with discrete window offset. Exp Fluids 26:513–523

    Article  Google Scholar 

  • Scarano F, Riethmuller ML (2000) Advances in iterative multigrid PIV image processing. Exp Fluids Suppl 29(7):S51–S60

    Google Scholar 

  • Smith SW (1999) The scientist and engineer’s guide to digital signal processing. California Technical Publishing, San Diego

    Google Scholar 

  • Soria J (1996) An investigation of the near wake of a circular cylinder using a video-based digital cross-correlation particle image velocimetry technique. Exp Therm Fluid Sci 12:221–233

    Article  Google Scholar 

  • Unser M (1999) Splines: a perfect fit for signal and image processing. IEEE Signal Process Mag 16(6):22–38

    Article  Google Scholar 

  • Unser M, Aldroubi A, Eden M (1993a) B-spline signal processing: Part I–theory. IEEE Trans Signal Process 41(2):821–832

    Article  MATH  Google Scholar 

  • Unser M, Aldroubi A, Eden M (1993b) B-spline signal processing: Part II–efficient design and applications. IEEE Trans Signal Process 41(2):834–848

    Article  MATH  Google Scholar 

  • Utami T, Blackwelder RF, Ueno T (1991) A cross-correlation technique for velocity field extraction from particulate visualization. Exp Fluids 10:213–223

    Article  Google Scholar 

  • Westerweel J (1993) Digital particle image velocimetry—theory and applications. PhD Thesis, Delft University

  • Westerweel J, Dabiri D, Gharib M (1997) The effect of a discrete window offset on the accuracy of cross-correlation analysis of digital PIV recordings. Exp Fluids 23:20–28

    Article  Google Scholar 

  • Willert CE, Gharib M (1991) Digital particle image velocimetry. Exp Fluids 10:181–193

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to T. Astarita.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Astarita, T. Analysis of interpolation schemes for image deformation methods in PIV: effect of noise on the accuracy and spatial resolution. Exp Fluids 40, 977–987 (2006). https://doi.org/10.1007/s00348-006-0139-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00348-006-0139-4

Keywords

Navigation