Optimal Combination of Techniques in Multiple Importance Sampling

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00221463" target="_blank" >RIV/68407700:21230/14:00221463 - isvavai.cz</a>
Result on the web
<a href="http://animation.szpt.edu.cn/vrcai/index.html" target="_blank" >http://animation.szpt.edu.cn/vrcai/index.html</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Optimal Combination of Techniques in Multiple Importance Sampling
Original language description
Multiple Importance Sampling (MIS) technique has been widely used in Computer Graphics in rendering algorithms. MIS is based on weighting several sampling techniques into a single estimator. When the combination weights are taken such that the sample contributions are balanced, i.e. they are the same for all techniques, it becomes balance heuristic. It has been used since its invention almost exclusively on equal sampling for all techniques. The question whether unequal sampling can give better variance, has raised till now little interest. Based on the properties of balance heuristic MIS as a weighted mixture of distributions, where weights are proportional to the number of samples, we obtain for this kind of integral an implicit closed formula for the sampling, where we get the minimum variance for MIS. We also take into account the cost of each sampling technique. Although this closed formula can not be written in an explicit way, we outline an iterative procedure to obtain the opti
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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