‘Advanced Global Illumination’reading notes 3

最新推荐文章于 2021-10-30 11:57:15 发布

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本文探讨了三种光照模型：随机松弛辐射度、离散随机游走辐射度及光子密度估计算法。通过对比不同模型的特点，如迭代过程、随机游走策略等，解析了它们在图像生成中的应用，并提出重要性采样等改进措施。

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I read Ch. 6 twice… Yes this part is abstruse.

1) Stocastic Relaxation Radiosity

Breadth first Monte Carlo iterative process. I love Jacob Iterative Method the most – by which, a image can be generated progressively. Isn’t it beautiful?
For curing image variance, Gathering for small patches, and Scattering for non-small patches.

2) Discrete Random Walk Radiosity

Comparing with #1, it is a depth first process, taking collision/survive/absortion test (Random Walk) as the stocastic estimation tool.

3) Photon Density Estimation Methods

It is a geometry free method, which I prefer the most. Unlike the above two those take mesh as the base, Photon-Density is a pixel based estimation method. But in essence I still consider it as a random walk process.

At last, several refinements as importance sampling is mentioned as one effective way for improving performance.

P.S. I would say this book is totally maths-based… good for researchers, but not so much for engineers..

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