Spatiotemporal Image Analysis for Fluid Flow Measurements

  • Christoph S. Garbe
  • Daniel Kondermann
  • Markus Jehle
  • Bernd Jähne
Part of the Notes on Numerical Fluid Mechanics and Multidisciplinary Design book series (NNFM, volume 106)

Abstract

In this chapter, a framework will be presented for measuring and modeling transport processes using novel visualization techniques and extended optical flow techniques for digital image sequence analysis. In this way, parameters besides the 2-D xy velocity components can be extracted concurrently from the acquired 2-D image sequences, such as wall shear rates and momentum transport close to boundaries, diffusion coefficients, and depth z in addition to the z velocity components. Depending on the application, particularly the temporal regularization can be enhanced, leading to stabilization of results and reduction of spatial regularization. This is frequently of high importance for flows close to boundaries. Results from applications will be presented from the fields of environmental and life sciences as well as from engineering.

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References

  1. 1.
    Andres, B., Hamprecht, F.A., Garbe, C.S.: Selection of local optical flow models by means of residual analysis. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 72–81. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Berthe, A., Kondermann, D., Jähne, B., Kertzscher, U.: The wall-piv measurement technique for near wall flow fields in biofluid mechanics. In: Nitsche, W., Dobriloff, C. (eds.) Imaging Measurement Methods for Flow Analysis. Springer, Heidelberg (2009)Google Scholar
  3. 3.
    Beushausen, V., Roetmann, K., Schmunk, W., Wellhausen, M., Garbe, C.: 2D-measurement technique for simultaneous quantitative determination of mixing ratio and velocity field in microfluidic applications. In: Nitsche, W., Dobriloff, C. (eds.) Imaging Measurement Methods for Flow Analysis. Springer, Heidelberg (2009)Google Scholar
  4. 4.
    Conn, A.R., Gould, N.I.M., Toint, P.L.: Trust-region methods. SIAM, Philadelphia (2000)MATHGoogle Scholar
  5. 5.
    Fick, A.E.: Über Diffusion. Annalen der Physik 94(4), 59–86 (1855)Google Scholar
  6. 6.
    Fleet, D., Weiss, Y.: Optical flow estimation. In: Paragios, N., Chen, Y., Faugeras, O. (eds.) Mathematical Models in Computer Vision: The Handbook, ch. 15, pp. 239–258. Springer, Heidelberg (2005)Google Scholar
  7. 7.
    Fourier, J.B.: Théorie analytique de la chaleur. In: Ouvres de Fourier, Gauthier-Villars et Fils, Paris, France (1822)Google Scholar
  8. 8.
    Garbe, C., Spies, H., Jähne, B.: Estimation of complex motion from thermographic image sequences. In: Thermosense, pp. 303–317 (2003)Google Scholar
  9. 9.
    Garbe, C.S.: Fluid flow estimation through integration of physical flow configurations. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 92–101. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Garbe, C.S., Degreif, K., Jähne, B.: Estimating the viscous shear stress at the water surface from active thermography. In: Garbe, C.S., Handler, R.A., Jähne, B. (eds.) Transport at the Air Sea Interface, pp. 223–239. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. 11.
    Garbe, C.S., Roetmann, K., Beushausen, V., Jähne, B.: An optical flow mtv based technique for measuring microfluidic flow in the presence of diffusion and taylor dispersion. Exp. in Fluids 44(3), 439–450 (2008)CrossRefGoogle Scholar
  12. 12.
    Jähne, B.: Digital Image Processing. Springer, Heidelberg (2005)Google Scholar
  13. 13.
    Jähne, B., Scharr, H., Körkel, S., Jähne, B., Haußecker, H., Geißler, P.: Principles of filter design. In: Handbook of Computer Vision and Applications, pp. 125–151, 2. Academic Press, London (1999)Google Scholar
  14. 14.
    Jehle, M., Jähne, B.: A novel method for three-dimensional three-component analysis of flows close to free water surfaces. Experiments in Fluids 44(3), 469–480 (2008)CrossRefGoogle Scholar
  15. 15.
    Jehle, M., Jähne, B., Kertzscher, U.: Direct estimation of the wall shear rate using parametric motion models in 3D. In: Franke, K., Müller, K.-R., Nickolay, B., Schäfer, R. (eds.) DAGM 2006. LNCS, vol. 4174, pp. 434–443. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  16. 16.
    Jolliffe, I.T.: Principal Component Analysis. Springer, Heidelberg (1986)Google Scholar
  17. 17.
    Knutsson, H., Westin, C.F.: Normalized and differential convolution: Methods for interpolation and filtering of incomplete and uncertain data. In: CVPR, New York City, pp. 515–516 (June 1993)Google Scholar
  18. 18.
    Kondermann, C., Kondermann, D., Garbe, C.: Postprocessing of optical flows via surface measures and motion inpainting. In: Rigoll, G. (ed.) DAGM 2008. LNCS, vol. 5096, pp. 355–364. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  19. 19.
    Kondermann, C., Mester, R., Garbe, C.: A statistical confidence measure for optical flows. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 290–301. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  20. 20.
    Roetmann, K., Schmunk, W., Garbe, C.S., Beushausen, V.: Micro-flow analysis by molecular tagging velocimetry and planar raman-scattering. Experiments in Fluids 44(3), 419–430 (2008)CrossRefGoogle Scholar
  21. 21.
    Rotter, F., Scholz, J., Müller, J., Wiersbinsky, T., Röhl, M., Ruhnau, P., Kondermann, D., Garbe, C., Hain, R., Beushausen, V.: Simultaneous, planar determination of fuel/air ratio and velocity field in single phase mixture formation processes. In: Nitsche, W., Dobriloff, C. (eds.) Imaging Measurement Methods for Flow Analysis. Springer, Heidelberg (2009)Google Scholar
  22. 22.
    Rudolph, I., Reyer, M., Nitsche, W.: Infrared-based visualization of wall shear stress distributions. In: Nitsche, W., Dobriloff, C. (eds.) Imaging Measurement Methods for Flow Analysis. Springer, Heidelberg (2009)Google Scholar
  23. 23.
    Scholz, J., Wiersbinski, T., Ruhnau, P., Kondermann, D., Garbe, C., Hain, R., Beushausen, V.: Double-pulse planar-lif investigations using fluorescence motion analysis for mixture formation investigation. Experiments in Fluids 45(4), 583–593 (2008)CrossRefGoogle Scholar
  24. 24.
    Tropea, C., Yarin, A.L., Foss, J.F. (eds.): Springer Handbook of Experimental Fluid Mechanics. Springer, Heidelberg (2007)Google Scholar
  25. 25.
    Van Huffel, S., Vandewalle, J.: The Total Least Squares Problem: Computational Aspects and Analysis. SIAM, Philadelphia (1991)MATHGoogle Scholar
  26. 26.
    Vlasenko, A., Schnörr, C.: Variational approaches to image fluid flow estimation with physical priors. In: Nitsche, W., Dobriloff, C. (eds.) Imaging Measurement Methods for Flow Analysis. Springer, Heidelberg (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Christoph S. Garbe
    • 1
  • Daniel Kondermann
    • 1
  • Markus Jehle
    • 1
  • Bernd Jähne
    • 1
  1. 1.Interdisciplinary Center for Scientific ComputingUniversity of Heidelberg 

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