Nonlinear models for representation, compression, and visualization of fluid flow images and velocimetry data

Nonlinear phase portraits are employed to represent the streamlines of scalar flow images generated by particle tracing experiments. The flow fields are decomposed into simple component flows based on the critical point behavior. A Taylor series model is assumed for the velocity components, and the model coefficients are computed by considering both local critical point and global flow field behavior. A merge and split procedure for complex flows is presented, in which patterns of neighboring critical point regions are combined and modeled. The concepts are extended to the compression of vector field data by using orthogonal polynomials derived from the Taylor series model. A critical point scheme and a block transform are presented. They are applied to velocity fields measured in particle image velocimetry experiments and generated by computer simulations.<<ETX>>

[1]  W Merzkirch,et al.  Techniques of Flow Visualization , 1987 .

[2]  Lambertus Hesselink,et al.  EVALUATION OF FLOW TOPOLOGY FROM NUMERICAL DATA , 1987 .

[3]  U. Dallmann.  Topological structures of three-dimensional vortex flow separation , 1983 .

[4]  A. Perry,et al.  Critical Points in Flow Patterns , 1975 .

[5]  Chiao-fe Shu,et al.  Direct estimation and error analysis for oriented patterns , 1993 .

[6]  A. Andronov,et al.  Qualitative Theory of Second-order Dynamic Systems , 1973 .

[7]  Ronald Adrian,et al.  High resolution measurement of turbulent structure in a channel with particle image velocimetry , 1991 .

[8]  M. S. Chong,et al.  A Description of Eddying Motions and Flow Patterns Using Critical-Point Concepts , 1987 .

[9]  Ramesh C. Jain,et al.  Computerized Flow Field Analysis: Oriented Texture Fields , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Al Globus,et al.  A tool for visualizing the topology of three-dimensional vector fields , 1991, Proceeding Visualization '91.

[11]  L. Lourenco.  Title: Recent Advances in LSV, PIV and PTV , 1993 .

[12]  M. S. Chong,et al.  A general classification of three-dimensional flow fields , 1990 .

[13]  Bruce A. Thomas,et al.  Image Models for 2-D Flow Visualization and Compression , 1994, CVGIP Graph. Model. Image Process..

[14]  Ramesh C. Jain,et al.  Vector field analysis for oriented patterns , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[15]  D. Jordan,et al.  Nonlinear ordinary differential equations (2nd ed.) , 1987 .

[16]  M. V. Dyke,et al.  An Album of Fluid Motion , 1982 .

[17]  Thomas Engelhardt,et al.  Coding of arbitrarily shaped image segments based on a generalized orthogonal transform , 1989, Signal Process. Image Commun..

[18]  Ramesh C. Jain,et al.  A linear algorithm for computing the phase portraits of oriented textures , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  C. Willert,et al.  Digital particle image velocimetry , 1991 .

[20]  Lambertus Hesselink,et al.  Digital Image Processing in Flow Visualization , 1988 .

[21]  Jerry D. Gibson,et al.  Digital coding of waveforms: Principles and applications to speech and video , 1985, Proceedings of the IEEE.

[22]  Lambertus Hesselink,et al.  Representation and display of vector field topology in fluid flow data sets , 1989, Computer.