High-quality particle-based volume rendering for large-scale unstructured volume datasets

High-quality particle-based volume rendering for large-scale unstructured volume datasets
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针对大规模非结构化体数据集的高质量基于粒子的体渲染

DOI:
10.1007/s12650-013-0158-1
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发表时间:
2013
期刊:
影响因子:
1.8
通讯作者:
K. Koyamada
K. Koyamada
中科院分区:
医学4区
文献类型:
--
作者:
Naohisa Sakamoto;Naoya Maeda;Takuma Kawamura;K. Koyamada

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摘要在本文中,我们提出了一种提高基于粒子的体绘制(PBVR)图像质量的技术。大规模非结构化体积数据集通常包含多个子体积,这些子体积不能按可见度排序。PBVR可以处理这种类型的体积数据集。当传递函数发生剧烈变化时,经常会出现采样失误,这可能会导致图像质量变差。为了减少高频传递函数引起的采样遗漏,我们提出了一种新的采样技术--分层采样。为了验证我们的技术的有效性,我们将所提出的技术应用于一个大规模的非结构化体积数据集,该数据集细分为多个子体积。
AbstractIn this article, we propose a technique for improving the image quality of particle-based volume rendering (PBVR). A large-scale unstructured volume dataset often contains multiple sub-volumes, which cannot be ordered by visibility. PBVR can handle this type of volume dataset. Sampling misses often occur when the transfer function undergoes drastic changes, which can result in poor image quality. To reduce sampling misses caused by the high-frequency transfer function, we develop a new sampling technique called “layered sampling”. To confirm the effectiveness of our technique, we apply the proposed technique to a large-scale unstructured volume dataset subdivided into multiple sub-volumes.Graphical Abstract
使用基于分布式粒子的体绘制实现大规模 CFD 仿真结果的可视化
DOI: 10.1260/1756-8315.2.2-3.73
发表时间: 2010
期刊: International Journal of Emerging Multidisciplinary Fluid Sciences
影响因子: --
作者:
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DOI: --
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影响因子: 4.2
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