Blue noise sampling using an SPH-based method

Authors: Jiang, M., Zhou, Y., Wang, R., Southern, R. and Zhang, J.

Editors: Marschner, S.

http://eprints.bournemouth.ac.uk/22610/

Journal: ACM Transactions on Graphics

ISSN: 1557-7368

We propose a novel algorithm for blue noise sampling inspired by the Smoothed Particle Hydrodynamics (SPH) method. SPH is a well-known method in fluid simulation -- it computes particle distributions to minimize the internal pressure variance. We found that this results in sample points (i.e., particles) with a high quality blue-noise spectrum. Inspired by this, we tailor the SPH method for blue noise sampling. Our method achieves fast sampling in general dimensions for both surfaces and volumes. By varying a single parameter our method can generate a variety of blue noise samples with different distribution properties, ranging from Lloyd's relaxation to Capacity Constrained Voronoi Tessellations ({CCVT}). Our method is fast and supports adaptive sampling and multi-class sampling. We have also performed experimental studies of the SPH kernel and its influence on the distribution properties of samples. We demonstrate with examples that our method can generate a variety of controllable blue noise sample patterns, suitable for applications such as image stippling and re-meshing.

This data was imported from Scopus:

Authors: Jiang, M., Zhou, Y., Wang, R., Southern, R. and Zhang, J.J.

http://eprints.bournemouth.ac.uk/22610/

Journal: ACM Transactions on Graphics

Volume: 34

Issue: 6

eISSN: 1557-7368

ISSN: 0730-0301

DOI: 10.1145/2816795.2818102

Copyright held by the Owner/Author. We propose a novel algorithm for blue noise sampling inspired by the Smoothed Particle Hydrodynamics (SPH) method. SPH is a well-known method in fluid simulation - it computes particle distributions to minimize the internal pressure variance. We found that this results in sample points (i.e., particles) with a high quality blue-noise spectrum. Inspired by this, we tailor the SPH method for blue noise sampling. Our method achieves fast sampling in general dimensions for both surfaces and volumes. By varying a single parameter our method can generate a variety of blue noise samples with different distribution properties, ranging from Lloyd's relaxation to Capacity Constrained Voronoi Tessellations (CCVT). Our method is fast and supports adaptive sampling and multi-class sampling. We have also performed experimental studies of the SPH kernel and its influence on the distribution properties of samples. We demonstrate with examples that our method can generate a variety of controllable blue noise sample patterns, suitable for applications such as image stippling and re-meshing.

This data was imported from Web of Science (Lite):

Authors: Jiang, M., Zhou, Y., Wang, R., Southern, R. and Zhang, J.J.

http://eprints.bournemouth.ac.uk/22610/

Journal: ACM TRANSACTIONS ON GRAPHICS

Volume: 34

Issue: 6

eISSN: 1557-7368

ISSN: 0730-0301

DOI: 10.1145/2816795.2818102

The data on this page was last updated at 18:34 on October 27, 2020.