光线追踪的分布式数据模型

J. Skyttä, T. Takala
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引用次数: 0

摘要

光线追踪是产生逼真图像的优越方法。它可以在图像形成中考虑到经典射线光学所涵盖的所有自然现象,而无需任何额外的建模工作。主要的缺点是它在计算机时间方面的高成本。在一台中等用途的通用计算机上,制作相当复杂场景的光线追踪图像需要很长时间。光线追踪的基本思想是模拟光线在整个模型空间中的路径的蛮力算法。由于没有使用模型的全局信息来预测射线与模型元素的相互作用,每条射线必须针对每个对象进行测试,并且大部分处理时间消耗在射线-物体相交计算上。在每个交点处,光线被分成反射和折射的部分,并被分成指向每个光源的光线,从而产生阴影。高质量的图像需要计算更多的像素,场景中元素的数量随模型复杂度线性增长,导致整个问题的计算复杂度急剧增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Distributed Data Model for Raytracing
Ray tracing is a superior method for producing realistic images. It can take into account all natural phenomena covered by classical ray optics in image formation, and that without any extra modeling effort. The main disadvantage is its high cost in terms of computer time. Production of ray traced images of reasonably complex scenes takes long in real time with a moderate general purpose computer [Whi80). The basic idea of ray tracing is the brute force algorithm for simulating the path of a ray of light in the whole model space. As no global information of the model is used to anticipate the interactions of the ray with model elements, every ray must be tested against every object and most of the processing time is consumed to ray-object intersection calculation. At each intersection found the ray is divided into reflected and refracted components and into a ray directed to each light source to produce shadows. Higher quality images need more pixels to be calculated and the number of elements in a scene grows linearly with model complexity, leading to steep increase of the computational complexity of the whole problem.
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