Stochastic rasterization may be used as a flexible volumetric sampling mechanism. By bounding and tessellating the sampling domain, uniform sampling distributions over an arbitrary domain can be efficiently generated in up to five dimensions. Sample placement allows pseudo-random, stratified random, or blue noise sampling. Random sampling with an adaptive density function may be achieved by adding one dimension.
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