Abstract
We have evaluated the performances of the following seven interpolation schemes used for window deformation in particle image velocimetry (PIV): the linear, quadratic, B-spline, cubic, sinc, Lagrange, and Gaussian interpolations. Artificially generated images comprised particles of diameter in a range 1.1 ≤ d p ≤ 10.0 pixel were investigated. Three particle diameters were selected for detailed evaluation: d p = 2.2, 3.3, and 4.4 pixel with a constant particle concentration 0.02 particle/pixel2. Two flow patterns were considered: uniform and shear flow. The mean and random errors, and the computation times of the interpolation schemes were determined and compared.
Similar content being viewed by others
Abbreviations
- a :
-
parameter in the cubic interpolation
- C :
-
particle density (particle/pixel2)
- d :
-
arbitrary value between 0 and 1 (pixel)
- d p :
-
particle diameter (pixel)
- f :
-
spatial frequency (pixel−1)
- f(x,y):
-
intensity data interpolated from the original image
- f 1 (x,y):
-
intensity data of the first image
- f 2 (x,y):
-
intensity data of the second image
- G 0 (x,b):
-
Gaussian function
- G P (x,b):
-
Pth derivative of the Gaussian function
- h(x):
-
one-dimensional impulse response function of a reconstruction filter
- h 2D (x,y):
-
two-dimensional impulse response function of a reconstruction filter
- H(f):
-
Fourier transform of the one-dimensional impulse response function of a reconstruction filter
- i :
-
integer horizontal position in the image (pixel)
- j :
-
integer vertical position in the image (pixel)
- k :
-
iteration number
- M :
-
total number of vectors
- N :
-
kernel size of an interpolation (pixel)
- U :
-
horizontal displacement in the uniform flow (pixel)
- \(\bar{U}\) :
-
mean of the measured displacements in the uniform flow (pixel)
- U exact :
-
exact displacement on the image for the uniform flow (pixel)
- U c :
-
horizontal displacement in the shear flow (pixel)
- \(\bar{U}_{c}\) :
-
mean of the measured displacements in the shear flow (pixel)
- U c,exact :
-
exact displacement on the image for the shear flow (pixel)
- \(\vec{V}(i,j)\) :
-
velocity vector at the (i,j) location (pixel, pixel)
- W :
-
size of a square interrogation window (pixel)
- γ2 :
-
parameter used in the second-order Gaussian interpolation
- γ6 :
-
parameter used in the sixth-order Gaussian interpolation
- Δx :
-
horizontal value to be determined through cross-correlation (pixel)
- Δy :
-
vertical value to be determined through cross-correlation (pixel)
- σ:
-
random error (pixel)
- ω:
-
shear rate (pixel/pixel)
- ω (i,j):
-
two-dimentional Gaussian windowing mask
References
Appledorn CR (1996) A new approach to the interpolation of sampled data. IEEE Trans Med Imaging 15(3):369–376
Astarita T, Cardone G (2005) Analysis of interpolation schemes for image deformation methods in PIV. Exp Fluids 38(2):233–243
Fincham A, Delerce G (2000) Advanced optimization of correlation imaging velocimetry algorithms. Exp Fluids Suppl:13–22
Gui L, Longo J, Stern F (2001) Bias of PIV measurement of turbulent flow and the mased correlation-based interrogation algorithm. Exp Fluids 30(1):27–35
Huang HT, Fiedler HE, Wang JJ (1993) Limitation and improvement of PIV. Part II: particle image distortion, a novel technique. Exp Fluids 15(4/5):263–273
Jambunathan K, Ju XY, Dobbins BN, Ashforth-Frost S (1995) An improved cross correlation technique for particle image velocimetry. Meas Sci Technol 6(5):507–514
Keane RD, Adrian RJ (1993) Theory of cross-correlation analysis of PIV images. Flow visualization and image analysis, pp 1–25
Lehmann TM, Gönner C, Spitzer K (1999) Survey: interpolation methods in medical image processing. IEEE Trans Med Imaging 18(11):1049–1075
Matsumoto M, Nishimura T (1998) Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Trans Model Comput Simul 8(1):3–30
Nogueira J, Lecuona A, Rodriguez PA (1999) Local field correction PIV: on the increase of accuracy of digital PIV systems. Exp Fluids 27(2):107–116
Okamoto K, Nishio S, Saga T, Kobayashi T (2000) Standard images for particle-image velocimetry. Meas Sci Technol 11(6):685–691
Raffel M, Willert CE, Kompenhans J (1998) Particle image velocimetry: a practical guide, Springer, Berlin Heidelberg New York, pp 134-146
Scarano F (2004a) A super-resolution particle image velocimetry interrogation approach by means of velocity second derivatives correlation. Meas Sci Technol 15(2):475–486
Scarano F (2004b) On the stability of iterative PIV image interrogation methods. In: Proceedings of 12th international symposium on appliacations of laser techniques to fluid mechanics, Lisbon, 12–15 July, 2004
Scarano F, Riethmuller ML (2000) Advances in iterative multigrid PIV image processing. Exp Fluids Suppl:51–60
Stanislas M, Okamoto K, Kähler C (2003) Main results of the first international PIV challenge. Meas Sci Technol 14(10):R63–R89
Tokumaru PT, Dimotakis PE (1995) Image correlation velocimetry. Exp Fluids 19(1):1–15
Tsuei L, Savas Ö (2000) Treatment of interfaces in particle image velocimetry. Exp Fluids 29(2):203–214
Wereley ST, Gui L (2003) A correlation-based central difference image correction (CDIC) method and application in a four-roll mill flow PIV measurement. Exp Fluids 34(1):42–51
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kim, B.J., Sung, H.J. A further assessment of interpolation schemes for window deformation in PIV. Exp Fluids 41, 499–511 (2006). https://doi.org/10.1007/s00348-006-0177-y
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00348-006-0177-y