计算机科学 ›› 2016, Vol. 43 ›› Issue (4): 294-298.doi: 10.11896/j.issn.1002-137X.2016.04.060

• 图形图像与模式识别 • 上一篇    下一篇

基于GPU的地震剖面图形快速绘制算法

邓博文,刘春松,吴凡贤,姚兴苗   

  1. 电子科技大学通信与信息工程学院 成都611731,电子科技大学通信与信息工程学院 成都611731,电子科技大学通信与信息工程学院 成都611731,电子科技大学资源与环境学院 成都611731
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(41104067)资助

Fast Graphical Rendering of Seismic Profile Algorithm Based on GPU

DENG Bo-wen, LIU Chun-song, WU Fan-xian and YAO Xing-miao   

  • Online:2018-12-01 Published:2018-12-01

摘要: 地震剖面图的绘制是二维地震数据可视化的基础。目前基于通用绘制引擎的地震剖面图绘制是在CPU上实现的,随着地震数据规模越来越大,传统绘制方法的绘制效率已经不能达到交互效率的要求,因此提出了一种地震剖面图快速绘制算法。该算法将地震数据的绘制和GPGPU技术相结合,利用GPU强大的并行计算能力实现图形光栅化处理。实验表明,在保证绘制效果的前提下,该方法极大地提高了绘制效率。

关键词: 地震数据,可视化,图形绘制,光栅化,GPU

Abstract: The drawing of seismic profile is the foundation of the visualization of 2D seismic data.Current method based on common rendering engine is complied on CPU,but with the increasing scale of seismic data,the conventional visua-lization method has been unable to meet the requirement of efficiency of interaction.This paper proposed a method to accelerate rendering seismic data graphics,which integrates graphical rendering and GPGPU technology.The graphical rasterization is implemented based on the powerful parallel computing capability of GPU.Experimental results indicate that,on the premise of ensuring imaging quality,large seismic data can be perfectly imaged in real time on a general PC platform.

Key words: Seismic data,Visualization,Graphical rendering,Rasterization,GPU

[1] Kehrer J,Hauser H.Visualization and Visual Analysis of Multifaceted Scientific Data:A Survey[J].IEEE Transactions on Visulization And Computer Graphics,2012,19(3):495-513
[2] Lyubomir G,Zagorchev.A Curvature-Adaptive Implicit Surface Reconstruction for Irregularly Spaced Points[J].IEEE Transaction on Visualtion & Computer Graphics,2011,8(9):1460-1473
[3] Zhu Liang-feng,Pan Xin,Wu Xin-cai,et al.Construct three-dimensional visualization methods geological fault model and implementation techniques [J].Journal of Software,2008,9 (8):2004-2017(in Chinese) 朱良峰,潘信,吴信才,等.地质断层三维可视化模型的构建方法与实现技术[J].软件学报,2008,9(8):2004-2017
[4] Wan Min,Wang Yu.Variational surface reconstruction based on Delaunay triangulation and graph cut[J].International Journal for Numerical Methods in Engineering,2011,5(2):2011
[5] Chen Cheng-kai,Correa H C, Ma K-L,et al.Visualizing 3DEarthquake Simulation Data[J].Computing in Science & Engineering,2010,13(6):52-63
[6] Xiao Han.Research studies of seismic data visualization [D].Changsha:Hunan University,2007:23-25(in Chinese) 肖汉.地震数据的可视化研究技术研究[D].长沙:湖南大学,2007:23-25
[7] Huang Dan.QT-based seismic data visualization research andapplication of [D].Chengdu:University of Electronic Science and Technology of China,2011:45-50(in Chinese) 黄丹.基于QT的地震数据可视化的研究及应用[D].成都:电子科技大学,2011:45-50
[8] Shi Zhi-xin.Study basic raster graphics generation algorithm[D].Jinan:Shandong University,2007(in Chinese) 石志昕.基本光栅图形生成算法研究[D].济南:山东大学,2007
[9] Xu Sai-hua,Zhang Er-hua.Parallel CUDA-based 3D data visualization[J].CT Theory and Applications,2011,0(1):47-54(in Chinese) 徐赛花,张二华.基于CUDA的三维数据并行可视化[J].CT理论与应用研究,2011,20(1):47-54
[10] Xie K,Wu P,Yang S.GPU and CPU cooperation parallel Visualisation for large seismic data[J].Electronics Letters,2010,46(17):1196-1197
[11] Patel D,Bruckner S,Viola I,et al.Seismic Volume Visualization for Horizon Extraction[C]∥IEEE Pacific Visualization Symposium.2010:73-80
[12] Xiao Han.The use of parallel GPU computing bilinear interpolation algorithm[J].Journal of Chinese Computer Systems,2010,1(11):2241-2245(in Chinese) 肖汉.利用GPU计算的双线性插值并行算法[J].小型微型计算机系统,2010,31(11):2241-2245
[13] NVIDIA CUDA.Programming Guide Version 3.0.http://developer.download.nvida.com/compute/cuda/3_0/toolkit/docs/NVIDIA_CUDA_ProgrammingGuide.pdf

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!