Low-discrepancy blue noise sampling

Abstract

We present a novel technique that produces two-dimensional low- discrepancy (LD) blue noise point sets for sampling. Using one- dimensional binary van der Corput sequences, we construct two- dimensional LD point sets, and rearrange them to match a target spectral profile while preserving their low discrepancy. We store the rearrangement information in a compact lookup table that can be used to produce arbitrarily large point sets. We evaluate our tech- nique and compare it to the state-of-the-art sampling approaches.