Data processing on scientific visualization

被引:0
|
作者
Bose, SK [1 ]
机构
[1] Bhabha Atom Res Ctr, Comp Div, Bombay 400085, Maharashtra, India
关键词
D O I
暂无
中图分类号
O469 [凝聚态物理学];
学科分类号
070205 ;
摘要
In early ages, in the absence of computer graphics scientists and engineers have used their imagination to interpret equations and printed numbers for a long time. This was very difficult, tedious and error prone, as the number of variables increases. Computer graphics provides an effective solution by converting these data into images that one can easily comprehend and assimilate instantaneously The basic purpose of computing is to gain knowledge inside into physical process. Ability to visualize plays an important role in gaining insight into the problem. For developing computer graphics programs on any platform one has to use industry standard graphics library. Now OpenGL is an emerging industry standard three dimensional graphics library provides advanced rendering features. OpenGL is designed to work efficiently in network environment. This means graphics program may exist in one computer (client) and display is on another computer (server). OpenGL program can be also apr the same computer where both client and server exist together. It is implemented on many different hardware platform. To achieve these there is no commands to handle windows. For handling windows one has to use native window calls. OpenGL provides basic geometric primitives,es like point, lines, polygons. Also it provides calls for rendering the object like flat shading, smooth shading with hidden surface removal, texture, fog etc.
引用
收藏
页码:88 / 90
页数:3
相关论文
共 50 条
  • [1] Parallel processing speeds visualization of scientific data
    Staley, Stephanie
    Bahrami, Ali
    [J]. Scientific Computing and Instrumentation, 2003, 20 (03): : 32 - 36
  • [2] Scientific Computing for Chemists: An Undergraduate Course. in Simulations, Data Processing, and Visualization
    Weiss, Charles J.
    [J]. JOURNAL OF CHEMICAL EDUCATION, 2017, 94 (05) : 592 - 597
  • [3] Collaborative scientific data visualization
    Ki, B
    Klasky, S
    [J]. CONCURRENCY-PRACTICE AND EXPERIENCE, 1997, 9 (11): : 1249 - 1259
  • [4] Collaborative scientific data visualization
    Ki, Byeongseob
    Klasky, Scott
    [J]. 1997, John Wiley & Sons Ltd, Chichester, United Kingdom (09):
  • [6] Data signatures and visualization of scientific data sets
    Wong, PC
    Foote, H
    Leung, R
    Adams, D
    Thomas, J
    [J]. IEEE COMPUTER GRAPHICS AND APPLICATIONS, 2000, 20 (02) : 12 - 15
  • [7] Scientific visualization of multidimensional data: Genetic likelihood visualization
    Park, JW
    Logue, M
    Ni, J
    Cremer, J
    Segre, A
    Vieland, V
    [J]. Current Trends in High Performance Computing and Its Applications, Proceedings, 2005, : 403 - 408
  • [8] SIGNAL-PROCESSING ASPECTS OF SCIENTIFIC VISUALIZATION
    MOORHEAD, RJ
    ZHU, ZF
    [J]. IEEE SIGNAL PROCESSING MAGAZINE, 1995, 12 (05) : 20 - 41
  • [9] Scientific Visualization: From Data to Insight
    Natarajan, Vijay
    [J]. RESONANCE-JOURNAL OF SCIENCE EDUCATION, 2013, 18 (07): : 615 - 629
  • [10] Spatial Storytelling and Scientific Data Visualization
    Bartzokas, Nick
    Parshina-Kottas, Yuliya
    Pisner, Noah
    Patanjali, Karthik
    [J]. PROCEEDINGS SIGGRAPH 2022 TALKS, 2022,