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Algorithms for animated volume visualization and three-dimensional image reconstruction.

机译:动画体积可视化和三维图像重建的算法。

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Three-dimensional (3D) linear projection is a procedure that projects the 3D object space onto a 2D plane. A set of parallel rays are defined that pass through the 3D object space. Points along each ray are sampled, and a transformation of the points is computed for each ray. The 3D planar projection is similar, except parallel planes are projected through the 3D data, onto a line. Three-dimensional parallel projection (linear or planar) finds numerous applications in the fields of computer graphics and image processing. For instance, scientific visualization of 3D data is achieved by projecting along rays to obtain a 2D frame for viewing. The reconstruction of 3D images from data collected by various means often involves 3D planar or linear projection.; In this research, we devise new fast linear and planar sampling algorithms for 3D parallel projection. Our new sampling algorithms operate in a recursive manner that is completely different from the conventional methods. They compute a set of linear or planar projections over a range of angles simultaneously, in far less time than required for the independent computation of each projection. In particular, our approximate linear projection algorithms are as much as a factor of {dollar}Theta(N){dollar} faster per projection than computing independently, and our approximate planar projection algorithm has a speedup of {dollar}Theta(Nsp2/log N{dollar}) over independent projections. Furthermore, the recursive sampling algorithms yield very efficient parallel algorithms. High efficiency is achieved by trading off some sampling accuracy--sample points are within {dollar}(sqrt{lcub}2{rcub}/2)log N - 1{dollar} units of the intended line or plane.; We next show how our algorithms can be applied to two computation-intensive problems from 3D imaging--animated volume visualization and 3D image reconstruction. We demonstrate that our sampling algorithms not only greatly speed up the 3D projection process, but also result in images of fairly good quality. The applications are implemented and evaluated on both sequential and parallel processing platforms.
机译:三维(3D)线性投影是将3D对象空间投影到2D平面上的过程。定义了一组穿过3D对象空间的平行射线。对沿每条射线的点进行采样,并对每条射线计算点的变换。 3D平面投影相似,不同之处在于平行平面通过3D数据投影到一条线上。三维平行投影(线性或平面)可在计算机图形和图像处理领域中找到许多应用。例如,通过沿射线投影以获得2D框架进行查看,可以实现3D数据的科学可视化。从通过各种方式收集的数据中重建3D图像通常涉及3D平面或线性投影。在这项研究中,我们为3D平行投影设计了新的快速线性和平面采样算法。我们的新采样算法以递归方式运行,这与传统方法完全不同。他们可以同时计算一系列角度范围内的线性或平面投影,所需时间远远少于独立计算每个投影所需的时间。特别是,我们的近似线性投影算法每个投影的{dollar} Theta(N){dollar}系数要比独立计算快得多,并且我们的近似平面投影算法的{dollar} Theta(Nsp2 / log N {dollar})超过独立投影。此外,递归采样算法产生了非常有效的并行算法。通过权衡一些采样精度可以实现高效率-采样点在目标直线或平面的{dollar}(sqrt {lcub} 2 {rcub} / 2)log N-1 {dollar}个单位内。接下来,我们将展示如何将我们的算法应用于来自3D成像的两个计算密集型问题-动画体积可视化和3D图像重建。我们证明了我们的采样算法不仅大大加快了3D投影过程,而且还可以产生质量相当好的图像。可以在顺序和并行处理平台上实施和评估应用程序。

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