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HanWei Shen, David L. Kao, "A New Line Integral Convolution Algorithm for Visualizing TimeVarying Flow Fields," IEEE Transactions on Visualization and Computer Graphics, vol. 4, no. 2, pp. 98108, AprilJune, 1998.  
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@article{ 10.1109/2945.694952, author = {HanWei Shen and David L. Kao}, title = {A New Line Integral Convolution Algorithm for Visualizing TimeVarying Flow Fields}, journal ={IEEE Transactions on Visualization and Computer Graphics}, volume = {4}, number = {2}, issn = {10772626}, year = {1998}, pages = {98108}, doi = {http://doi.ieeecomputersociety.org/10.1109/2945.694952}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Visualization and Computer Graphics TI  A New Line Integral Convolution Algorithm for Visualizing TimeVarying Flow Fields IS  2 SN  10772626 SP98 EP108 EPD  98108 A1  HanWei Shen, A1  David L. Kao, PY  1998 KW  Flow visualization KW  vector field visualization KW  image convolution KW  line integral convolution KW  flow animation KW  unsteady flows KW  texture synthesis KW  parallel algorithm. VL  4 JA  IEEE Transactions on Visualization and Computer Graphics ER   
Abstract—New challenges on vector field visualization emerge as timedependent numerical simulations become ubiquitous in the field of computational fluid dynamics (CFD). To visualize data generated from these simulations, traditional techniques, such as displaying particle traces, can only reveal flow phenomena in preselected local regions and, thus, are unable to track the evolution of global flow features over time. This paper presents a new algorithm, called UFLIC (Unsteady Flow LIC), to visualize vector data in unsteady flow fields. Our algorithm extends a texture synthesis technique, called Line Integral Convolution (LIC), by devising a new convolution algorithm that uses a timeaccurate value scattering scheme to model the texture advection. In addition, our algorithm maintains the coherence of the flow animation by successively updating the convolution results over time. Furthermore, we propose a parallel UFLIC algorithm that can achieve high loadbalancing for multiprocessor computers with shared memory architecture. We demonstrate the effectiveness of our new algorithm by presenting image snapshots from several CFD case studies.
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