  Based on the seminal work on Array-RQMC methods and rank-1 lattice sequences
by Pierre L'Ecuyer and collaborators, we introduce efficient deterministic
algorithms for image synthesis. Enumerating a low discrepancy sequence along
the Hilbert curve superimposed on the raster of pixels of an image, we achieve
noise characteristics that are desirable with respect to the human visual
system, especially at very low sampling rates. As compared to the state of the
art, our simple algorithms neither require randomization, nor costly
optimization, nor lookup tables. We analyze correlations of space-filling
curves and low discrepancy sequences, and demonstrate the benefits of the new
algorithms in a professional, massively parallel light transport simulation and
rendering system.
