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Variance and variation reduction technique in the quasi-Monte Carlo global illumination algorithm

Kozankiewicz P.

Machine Graphics and Vision

2000

Vol. 9, No. 1/2

289-296

The accuracy of the Monte Carlo and quasi-Monte Carlo algoriths depends on variance and variation in the sense of Hardy-Krause of the integral. This paper contains an error estimation of the quasi-Monte Carlo algorithm for some discontinuous functions that appear in radiosity and global illumination computation. Also an algorith that transforms the integral to reduce variance and variation is presented. It takes advantage of the BRDF properties and it can be used with diffuse and non-diffuse environments.

Non-diffuse, random-walk radiosity algorithm with linear basis functions

Szirmay-Kalos L., Foris T., Purgathofer W.

Machine Graphics and Vision

1998

Vol. 7, No. 1/2

475-484

This paper presents an efficient method to solve the general rendering equation, using a combined finite element and quasi-random walk approach. Applying point collocation method, the surfaces are decomosed into planar patches where the directional distribution of the radiance is assumed to be a linear combination of the disrtibutions at the vertices. The direction dependet radiance function of the vertces is then computed by random of quasi-random walk.