Russian-roulette is one of the most important techniques to compute infinite
dimensional integrals in an unbiased way. However, Russian roulette is also
responsible for adding large amount of noise. This paper examines Russian
roulette and a related problem, the sampling of combined BRDFs and proposes two
improvements that can reduce the additional noise of Russian-roulette and
random elementary BRDF selection, keeping also the unbiasedness of the method.
The first improvement takes advantage that the light transfer is computed on
several wavelengths simultaneously, thus the distribution of the energy on the
wavelengths should be more precisely taken into account when Russian-roulette
is made to terminate the walk or to select randomly from the elementary BRDFs.
The second improvement gets rid of the fundamental assumption of Russian
roulette that the contribution is zero when the walk is terminated. If we have
a better estimation for the incoming radiance at this case, this estimation can
be used instead, which can significantly reduce the additional noise.
Keywords: Global illumination, random walks, Russian-roulette, spectral rendering, photon map