基于八叉树编码的CUDA光线投射算法  

A ray casting algorithm based on octree encoding and CUDA

作　　者：康健超[1] 康宝生[1] 冯筠[1] 王国栋[1] 赵建东[1] 唐斌[1] 

机构地区：[1]西北大学信息科学与技术学院,陕西西安710127

出　　处：《西北大学学报（自然科学版）》2012年第1期36-41,共6页Journal of Northwest University（Natural Science Edition）

基　　金：国家自然科学基金资助项目(60873095);西北大学研究生创新教育基金资助项目(09YZZ66;10YSY02)

摘　　要：目的针对传统的GPU光线投射算法绘制效果差,绘制效率低的问题,在CUDA架构上对光线投射算法进行优化和加速。方法首先采用八叉树对体数据进行编码,有效地剔除体数据中对重建图像无贡献的部分;其次,将体数据绑定到三维纹理上,根据体数据大小分配线程,每条光线与体数据求交时采用并行计算;最后,在CUDA内核中实现光线投射算法。结果仿真实验结果表明文中算法可以将传统GPU光线投射算法的绘制速度提高7～15倍,并增强算法的绘制效果。结论算法对传统的GPU光线投射算法的绘制速度和效果都有提高。Aim For the low sampling efficiency and poor drawing efficiency in the traditional ray casting algorithm based on GPU, the algorithm is used to optimize and acceleratien in CUDA structure. Methods Firstly, the volume data are encoded by octree, it can eliminate the parts which do not contribute to reconstructed image efficiently. Secondly the data is bound to 3D texture and the thread is distributed according to the size of volume data, par- allel computing is used when finding out the intersection of each of the light and the volume data. Finally the ray casting algorithm is realized in CUDA kernel. Results The experimental results show that the algorithm can increase the speed by 7 - 15 times, and enhance the algorithm. Conclusion The algorithm can improve the speed and effect of traditional raycasting algorithm based on GPU.

关 键 词：光线投射算法 通用并行计算架构 八叉树 三维纹理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]