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On-the-fly processing of compressed volume data.

机译:动态处理压缩量数据。

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摘要

In this thesis, we explore several approaches to integrate compression and rendering into a single processing pipeline. The first integration scheme applies only to regular volume data sets, and performs rendering directly on compressed data sets without any decompression at all. This scheme thus reduces the data loading time and the memory footprint size, and at the same time avoids the decompression overhead completely.; The second integration applies to irregular volume data sets where volume rendering can be performed on the fly during decompression. In this scheme, the renderer can start to work immediately after the decompressor outputs the first tetrahedron, therefore the start-up latency is significantly reduced. As data sets are brought into memory in their compressed form, the data loading time is minimized. Together with a garbage collection mechanism that frees tetrahedra immediately after they have made their contributions, we further reduced the peak memory footprint size, which in turn, leads to further performance improvement. This reduction in memory foot-print size is especially helpful for those data sets whose peak memory requirements exceed the physical memory size, i.e., out-of-core rendering applications.; To address the rendering performance issue, volume simplification represents a promising approach as it provides a mechanism to trade quality for performance. However, volume simplification is mostly performed independently of volume compression. We have developed an algorithm to integrate volume simplification with volume compression, thus making it possible to perform volume simplification and rendering on the fly during volume decompression. Through this pipeline-like structure, each tetrahedron goes through the decompression stage, simplification stage, and rendering stage, if it is not simplified away. However, to be able to support “time-critical” rendering which enables interactive or even real-time volume data browsing, this integration scheme alone is not sufficient, because of the decompression overhead. To avoid decompressing a whole data set each time, we develop a multi-resolution pre-simplification mechanism to correctly determine the corresponding simplification ratio for a given frame rate, and eventually deliver the frame rate accordingly.; To demonstrate how volume compression can also be integrated into other applications as well, we have also developed an algorithm that combines volume compression with iso-surface extraction into a one-pass algorithm. (Abstract shortened by UMI.)
机译:在本文中,我们探索了几种将压缩和渲染集成到单个处理管道中的方法。第一种集成方案仅适用于常规体积数据集,并且直接对压缩数据集执行渲染,而根本不进行任何解压缩。因此,该方案减少了数据加载时间和存储器占用空间,同时完全避免了解压缩开销。第二次集成适用于不规则的体积数据集,其中在解压缩期间可以即时执行体积渲染。在此方案中,渲染器可以在解压缩器输出第一个四面体之后立即开始工作,因此,启动延迟显着减少。随着数据集以其压缩形式进入内存,数据加载时间得以最小化。连同垃圾回收机制一起使用,在四面体做出贡献后立即释放四面体,我们进一步减小了峰值内存占用空间大小,从而进一步提高了性能。减少内存占用空间的大小对于峰值内存需求超过物理内存大小的那些数据集(即核外渲染应用程序)特别有用。为了解决渲染性能问题,简化体积代表了一种有前途的方法,因为它提供了一种以质量换取性能的机制。但是,体积简化通常独立于体积压缩执行。我们开发了一种将体积简化与体积压缩集成在一起的算法,从而可以在体积解压缩过程中即时执行体积简化和渲染。通过这种流水线状的结构,每个四面体都要经过减压阶段,简化阶段和渲染阶段(如果没有简化的话)。但是,为了能够支持交互式或什至实时的体积数据浏览的“时间紧迫”渲染,仅此集成方案是不够的,因为其解压缩开销很大。为了避免每次对整个数据集进行解压缩,我们开发了一种多分辨率预简化机制,以针对给定的帧速率正确确定相应的简化比例,并最终相应地提供帧速率。为了演示如何将体积压缩也可以集成到其他应用程序中,我们还开发了一种算法,该算法将体积压缩与等值面提取相结合,形成了单遍算法。 (摘要由UMI缩短。)

著录项

  • 作者

    Yang, Chuan-kai.;

  • 作者单位

    State University of New York at Stony Brook.;

  • 授予单位 State University of New York at Stony Brook.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 133 p.
  • 总页数 133
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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