  In order to efficiently sample specular-diffuse-glossy and
glossy-diffuse-glossy transport phenomena, Tokuyoshi and Harada introduced
hierarchical Russian roulette, a smart algorithm that allows to compute the
minimum of the random numbers associated to leaves of a tree at each internal
node. The algorithm is used to efficiently cull the connections between the
product set of eye and light vertices belonging to large caches of eye and
light subpaths produced through bidirectional path tracing. The original
version of the algorithm is entirely based on the generation of semi-stratified
pseudo-random numbers. Our paper proposes a novel variant based on
deterministic blue-noise dithered Quasi Monte Carlo samples.
