Flow Visualization Based on Enhanced Streamline Line Integral Convolution

doi:10.16182/j.issn1004731x.joss.201612008

Abstract

Abstract: In order to show the flow information clearly and reduce the calculation of linear integral convolution, an enhanced streamline linear integral convolution algorithm was proposed. The generation of streamlines were improved. Critical points were detected and the points’ area with a gradient fill was generated. Combined two integration methods in different areas, the integration step was updated adaptively. Utilizing the parallelism of GPU and GLSL (OpenGL shading language), the algorithm further improved the sharpness of the output image. Experiments show that the improved linear integral convolution algorithm posses both the speedability and the precision. And the flow visualization of the river and hurricane with this improved method can show the flow field information intuitively.

Key words: flow field visualization, line integral convolution, critical points detection, GPU

CLC Number:

TP391

Han Min, Zhang Haichao, Bian Maosong, Zheng Danchen. Flow Visualization Based on Enhanced Streamline Line Integral Convolution[J]. Journal of System Simulation, 2016, 28(12): 2933-2938.

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