Sampling Algorithms

Jittering, motion blurring, area light sources, or the depth-of-field lens effect are based on multiple sampling with varying the sample locations in time, 2D or 3D space. mental ray offers a proprietary implementation of the Quasi-Monte Carlo method for achieving these variations. Sample locations in time, 2D and 3D space are deterministically chosen on fixed points that ensure optimal coverage of the sample space. The algorithm is similar to fixed-raster algorithms, but avoids the regular lattice appearance of such algorithms. The resulting images are identical if the scene is re-rendered with the same options due to the deterministic nature of the algorithm.

Quasi-Monte Carlo methods can be succinctly described as strictly deterministic sampling methods. Determinism enters in two ways, namely, by working with deterministic points rather than random samples and by the availability of deterministic error bounds (Niederreiter92).

Unified Sampling 3.9

The unified sampling interface provides a simple and consistent set of controls for the various different rendering algorithms and sampling strategies, including adaptive sampling for ray tracing, fixed sampling for the rasterizer, and progressive rendering. The original controls and settings remain active until unified sampling has been enabled in the rendering options of the scene.

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