@article{1aff7368a1564c45824e662417fb9843,
title = "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 technique and compare it to the state-of-the-art sampling approaches.",
keywords = "Blue Noise, Low Discrepancy, Monte Carlo, Quasi-Monte Carlo, Sampling",
author = "Ahmed, {Abdalla G.M.} and H{\'e}l{\`e}ne Perrier and David Coeurjolly and Victor Ostromoukhov and Jianwei Guo and Yan, {Dong Ming} and Hui Huang and Oliver Deussen",
note = "Funding Information: We thank the anonymous reviewers for their detailed feedback to improve the paper. Thanks to Jean-Yves Franceschi and Jonathan Dupuy for reviewing an earlier version of the paper. This project was supported in part by Deutsche Forschungsgemeinschaft Grant (DE-620/22-1), French ANR Excellence Chair (ANR-10-CEXC-002-01) and CoMeDiC (ANR-15-CE40-0006), 973 Program (2015CB352501), National Foreign 1000 Plan (WQ201344000169), National Natural Science Foundation of China (61372168, 61620106003, 61331018), GD Leading Talents Plan (00201509), GD Science and Technology Program (2014B050502009, 2014TX01X033, 2015A030312015, 2016A050503036), and SZ Innovation Program (JCYJ20151015151249564). Publisher Copyright: {\textcopyright} 2016 Copyright held by the owner/author(s). Publication rights licensed to ACM.",
year = "2016",
month = nov,
doi = "10.1145/2980179.2980218",
language = "English (US)",
volume = "35",
journal = "ACM transactions on graphics",
issn = "0730-0301",
publisher = "Association for Computing Machinery",
number = "6",
}