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Proceedings Paper

Enhanced line integral convolution with flow feature detection
Author(s): Arthur Okada; David L. Kao
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Paper Abstract

The line integral convolution (LIC) method, which blurs white noise textures along a vector field, is an effective way to visualize overall flow patterns in a 2D domain. The method produces a flow texture image based on the input velocity field defined in the domain. Because of the nature of the algorithm, the texture image tends to be blurry. This sometimes makes it difficult to identify boundaries where flow separation and re-attachments occur. We present techniques to enhance LIC texture images and use colored texture images to highlight flow separation and re- attachment boundaries. Our techniques have been applied to several flow fields defined in 3D curvilinear multi-block grids and scientists have found the results to be very useful.

Paper Details

Date Published: 9 April 1997
PDF: 12 pages
Proc. SPIE 3017, Visual Data Exploration and Analysis IV, (9 April 1997); doi: 10.1117/12.270314
Show Author Affiliations
Arthur Okada, Parametric Technology Corp. (United States)
David L. Kao, NASA Ames Research Ctr. (United States)

Published in SPIE Proceedings Vol. 3017:
Visual Data Exploration and Analysis IV
Georges G. Grinstein; Robert F. Erbacher, Editor(s)

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