›› 2015, Vol. 30 ›› Issue (3): 439-452.doi: 10.1007/s11390-015-1535-0

Special Issue: Surveys; Computer Graphics and Multimedia

• Special Section on Computational Visual Media • Previous Articles     Next Articles

A Survey of Blue-Noise Sampling and Its Applications

Dong-Ming Yan1,2(严冬明), Member, CCF, ACM, Jian-Wei Guo2(郭建伟), Bin Wang3(王斌), Xiao-Peng Zhang2(张晓鹏), Peter Wonka1,4   

  1. 1. Visual Computing Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia;
    2. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;
    3. School of Software, Tsinghua University, Beijing 100084, China;
    4. Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, U.S.A.
  • Received:2015-03-09 Revised:2015-04-02 Online:2015-05-05 Published:2015-05-05
  • About author:Dong-Ming Yan is a research scientist at King Abdullah University of Science and Technology (KAUST), and he is also an associate professor at National Laboratory of Pattern Recognition (NLPR), the Institute of Automation of the Chinese Academy of Sciences (CASIA), Beijing. He received his Ph.D. degree in computer science from Hong Kong University in 2010, and M.S. and B.S. degrees in computer science and technology from Tsinghua University in 2005 and 2002, respectively. His research interests include computer graphics, geometric processing and visualization.
  • Supported by:

    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.

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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