计算机科学 ›› 2013, Vol. 40 ›› Issue (9): 257-261.

• 图形图像与模式识别 • 上一篇    下一篇

二维LIC矢量场可视化算法的研究及改进

詹芳芳,胡伟,袁国栋   

  1. 北京化工大学信息科学与技术学院 北京100029;北京化工大学信息科学与技术学院 北京100029;清华大学计算机科学与技术系 北京100084
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家高技术研究发展计划(863计划)(2010AA012402),国家自然科学基金项目(61003132)资助

Improvement of 2D LIC Algorithm for Vector Field Visualization

ZHAN Fang-fang,HU Wei and YUAN Guo-dong   

  • Online:2018-11-16 Published:2018-11-16

摘要: 线积分卷积(LIC)是一种针对矢量场的可视化方法。针对二维空间上的LIC算法进行了研究并提出了改进。首先,针对某些二维矢量场在用户关注区域矢量大小比较接近的问题,采用非线性的颜色映射法进行处理,最终的可视化结果可以突出用户感兴趣区域的矢量场特征。其次,从原始LIC算法的串行计算任务中提取出4个可以并行计算的子模块,并依托NVIDIA的CUDA架构实现了颜色增强LIC法的硬件加速。结果表明,加速后算法的加速比随着输入矢量场分辨率的增加而增加。因此,该算法适用于高分辨率二维矢量场的交互式可视化,且没有特别高的硬件要求,通用性较好。总之,新的算法较原始算法在视觉效果和性能上都有所改进。

关键词: 矢量场可视化,线积分卷积,颜色增强,GPU加速 中图法分类号TP391.41文献标识码A

Abstract: Line integral convolution(LIC)is a method for vector field visualization.This paper presented an improved LIC technique for 2D vector field.Firstly,focused on the problem that some vector field’s magnitude is too similar in regions of interest,we used nonlinear color mapping method to deal with it,and the final visualization result can highlight the vector field’s characteristics in regions of interest.Secondly,we extracted four parallel sub-modules from the original LIC serial computing tasks and implemented color enhanced LIC’s hardware acceleration relying on NVIDIA’s CUDA architecture.The results show that,with the increase of the input vector fields’ resolution,the speed of the accelera-ted algorithm increases as well.Therefore,the accelerated algorithm implemented in this paper can be well applied to interactive visualization of high-resolution 2D vector fields,and it has a good versatility,demanding no high hardware requirements.To conclude,the new method can improve visual quality with better performance.

Key words: Vector field visualization,Line integral convolution,Color enhancing,GPU acceleration

[1] Laramee R S,Hauser H,Doleisch H,et al.The state of the art in flow visualization:dense and texture-based techniques[J].Computer Graphics Forum,2004,3(2):203-221
[2] Stalling D,Hege H.Fast and resolution independent line integral convolution[C]∥Proceedings of the ACM SigGraph’95.New York ACM SIGGRAPH,1995:249-256
[3] Van Wijk J J.Spot noise:texture synthesis for data visualization[J].Computer Graphics,1991,5(4):309-318
[4] Cabral B,Leedom C.Imaging vector fields using line integral convolution[J].Computer Graphics,1993,27(4):263-272
[5] Leeuw W D,Liere R V.Comparing LIC and spot noise[C]∥Proceedings of IEEE Visualization’98,IEEE Computer Society.1998:359-365
[6] 陆剑锋,潘志庚,张明敏.基于图像对比度数量映射的矢量场可视化算法[J].系统仿真学报,2004,6(7):1502-1505
[7] 张文耀,蒋凌霜.基于HSV颜色模型的二维流场可视化[J].北京理工大学学报,2010,0(3):302-306
[8] 陈丽娜.基于线积分卷积可视化矢量场大小的研究[J].陕西理工学院学报:自然科学版,2009,5(3):50-52,4
[9] 朱宏玮,姜国华,王宝智.矢量场可视化线积分卷积方法研究与系统设计[J].计算机应用与软件,2010,7(4)
[10] Zckler M,Stalling D,Hege H.Parallel line integral convolution[J].Parallel Computing,1997,3(7):975-989
[11] Hlawatsch M,Sadlo F,Weiskopf D.Hierarchical line integration[J].IEEE Transactions on Visualization and Computer Gra-phics,2011,7(8):1148-1163
[12] NVIDIA Corporation.NVIDIA CUDA C programming guide[EB/OL].http://developer.nvidia.com/nvidia-gpu-computing-documentation,2012-07-06

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