基于八叉树自适应体归并的光线跟踪加速结构

发布时间：2018-03-07 00:05

本文选题：光计算　切入点：光学数据处理　出处：《光学学报》2017年01期 　论文类型：期刊论文

【摘要】：针对光线跟踪算法计算量大和运行效率低的问题,提出了一种采用八叉树自适应体归并(OAVM)的光线跟踪加速结构。该结构将八叉树模型的空节点自适应地聚集为包围体,尽可能地减小了光线与空白节点的求交次数。基于OAVM的一种多级八叉树结构的特点,提出了采用Morton码对各层级的所有节点分别进行编码的算法,该结构所采用的存储方式和邻域查询算法有效减小了指针数量,避免了递归搜索。同时,该算法可以有效处理大规模动态场景的局部更新问题。基于Liang-Barsky算法,光线相交测试的计算速度得到提升。实验结果表明,和传统结构算法相比,所提出算法的指针总数平均减少了54.45%,光线相交测试时间平均缩短了52.37%,大幅加快了相交测试速度,提升了场景的渲染效率。
[Abstract]:Aiming at the problems of large computation and low efficiency of ray-tracking algorithm, an accelerated ray-tracing structure using octree adaptive body merging (OAVM) is proposed. The structure adaptively aggregates the empty nodes of the octree model into a bounding body. The number of intersection between light and blank nodes is reduced as much as possible. Based on the characteristics of a multilevel octree structure of OAVM, an algorithm using Morton codes to encode all nodes at each level is proposed. The storage method and neighborhood query algorithm used in this structure can effectively reduce the number of pointers and avoid recursive search. At the same time, the algorithm can effectively deal with the local updating problem of large-scale dynamic scenes. The experimental results show that compared with the traditional algorithm, the total number of pointers in the proposed algorithm is reduced by an average of 54.45 points, and the test time of the light intersection test is reduced by 52.37 on average, and the speed of the intersecting test is greatly accelerated. Improved rendering efficiency of the scene.
【作者单位】：海军航空工程学院电子信息工程系;空军航空大学航空航天情报系;
【基金】：吉林省自然科学基金(20130101069JC) 军内武器装备重点科研项目(KJ2012240)
【分类号】：O43

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