A Survey of Blue-Noise Sampling and Its Applications

Dong Ming Yan; Jian Wei Guo; Bin Wang; Xiao Peng Zhang; Peter Wonka

doi:10.1007/s11390-015-1535-0

A Survey of Blue-Noise Sampling and Its Applications

Dong Ming Yan, Jian Wei Guo, Bin Wang, Xiao Peng Zhang, Peter Wonka

Research output: Contribution to journal › Article › peer-review

57 Scopus citations

Abstract

In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.

Original language	English (US)
Pages (from-to)	439-452
Number of pages	14
Journal	Journal of Computer Science and Technology
Volume	30
Issue number	3
DOIs	https://doi.org/10.1007/s11390-015-1535-0
State	Published - May 1 2015

Keywords

Lloyd relaxation
Poisson-disk sampling
blue-noise sampling
remeshing
rendering

ASJC Scopus subject areas

Software
Theoretical Computer Science
Hardware and Architecture
Computer Science Applications
Computational Theory and Mathematics

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10.1007/s11390-015-1535-0

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title = "A Survey of Blue-Noise Sampling and Its Applications",

abstract = "In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.",

keywords = "Lloyd relaxation, Poisson-disk sampling, blue-noise sampling, remeshing, rendering",

author = "Yan, {Dong Ming} and Guo, {Jian Wei} and Bin Wang and Zhang, {Xiao Peng} and Peter Wonka",

note = "Funding Information: This work was partially supported by the National Natural Science Foundation of China under Grant Nos. 61372168, 61373071, 61372190, and 61331018, the Scientific Research Foundation for the Returned Overseas Chinese Scholars of State Education Ministry of China, the Visual Computing Center at King Abudullah University of Science and Technology (KAUST), and the Open Funding Project of the State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, under Grant Nos. BUAA-VR-15KF-06 and BUAA-VR-14KF-10. Publisher Copyright: {\textcopyright} 2015, Springer Science+Business Media New York.",

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doi = "10.1007/s11390-015-1535-0",

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AU - Wang, Bin

AU - Zhang, Xiao Peng

AU - Wonka, Peter

N1 - Funding Information: This work was partially supported by the National Natural Science Foundation of China under Grant Nos. 61372168, 61373071, 61372190, and 61331018, the Scientific Research Foundation for the Returned Overseas Chinese Scholars of State Education Ministry of China, the Visual Computing Center at King Abudullah University of Science and Technology (KAUST), and the Open Funding Project of the State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, under Grant Nos. BUAA-VR-15KF-06 and BUAA-VR-14KF-10. Publisher Copyright: © 2015, Springer Science+Business Media New York.

PY - 2015/5/1

Y1 - 2015/5/1

N2 - In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.

AB - In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.

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KW - Poisson-disk sampling

KW - blue-noise sampling

KW - remeshing

KW - rendering

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A Survey of Blue-Noise Sampling and Its Applications

Abstract

Keywords

ASJC Scopus subject areas

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