使用自适应重采样方案的实时体绘制架构,用于并行和透视投影

M. Ogata, T. Ohkami, H. Lauer, H. Pfister
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引用次数: 15

摘要

本文描述了一种采用自适应重采样方案的对象顺序实时体绘制体系结构,以统一的并行管道方式对并行投影和透视投影进行重采样操作。与平行投影不同,由于透视光线发散,透视投影需要可变的重采样结构。为了解决这个问题,我们提出了一种自适应的流水线卷积块,利用分辨率水平来进行重采样操作,以保持并行流水线结构的规则性。我们还建议使用针对不同网格分辨率级别准备的多分辨率数据集来约束卷积操作。所提出的卷积块使用收缩数组结构组织,它可以很好地与分布式倾斜内存一起用于无冲突的体素访问。我们给出了我们的软件模拟器的一些实验结果,并讨论了重要的技术问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A real-time volume rendering architecture using an adaptive resampling scheme for parallel and perspective projections
The paper describes an object order real time volume rendering architecture using an adaptive resampling scheme to perform resampling operations in a unified parallel pipeline manner for both parallel and perspective projections. Unlike parallel projections, perspective projections require a variable resampling structure due to diverging perspective rays. In order to address this issue, we propose an adaptive pipelined convolution block for resampling operations using the level of resolution to keep the parallel pipeline structure regular. We also propose to use multi resolution datasets prepared for different levels of grid resolution to bound the convolution operations. The proposed convolution block is organized using a systolic array structure, which works well with a distributed skewed memory for conflict free accesses of voxels. We present the results of some experiments with our software simulators of the proposed architecture and discuss important technical issues.
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