辐射的边界和误差估计

Dani Lischinski, Brian E. Smits, D. Greenberg
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引用次数: 131

摘要

我们提出了一种方法来确定后验界和估计的局部和总误差的辐射解决方案。为了可靠地判断解的可接受性,获得总误差的范围和估计的能力是至关重要的。局部误差的实际估计提高了自适应辐射算法的效率,如分层辐射,通过指示哪里需要自适应改进。首先,我们描述了一种分层辐射算法,该算法计算精确辐射函数的保守下界和上界以及近似解。这些边界考虑了由于相互反射引起的误差传播,并提供了误差的保守上界。我们还描述了同一算法的非保守版本,它能够计算更严格的边界,从中可以获得更真实的误差估计。最后,我们推导出了一个特定相互作用对总误差影响的表达式。这产生了一种新的误差驱动的分层辐射细化策略,该策略优于亮度加权细化。
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Bounds and error estimates for radiosity
We present a method for determining a posteriori bounds and estimates for local and total errors in radiosity solutions. The ability to obtain bounds and estimates for the total error is crucial fro reliably judging the acceptability of a solution. Realistic estimates of the local error improve the efficiency of adaptive radiosity algorithms, such as hierarchical radiosity, by indicating where adaptive refinement is necessary. First, we describe a hierarchical radiosity algorithm that computes conservative lower and upper bounds on the exact radiosity function, as well as on the approximate solution. These bounds account for the propagation of errors due to interreflections, and provide a conservative upper bound on the error. We also describe a non-conservative version of the same algorithm that is capable of computing tighter bounds, from which more realistic error estimates can be obtained. Finally, we derive an expression for the effect of a particular interaction on the total error. This yields a new error-driven refinement strategy for hierarchical radiosity, which is shown to be superior to brightness-weighted refinement.
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