Yan DM, Guo JW, Wang B et al. A survey of blue-noise sampling and its applications. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 30(3): 439–452 May 2015. DOI 10.1007/s11390-015-1535-0 A Survey of Blue-Noise Sampling and Its Applications 1,2 2 3 ý² Àïå Ê Dong-Ming Yan (î ), Member, CCF, ACM, Jian-Wei Guo ( ), Bin Wang ( ) 2 1,4 ¡· Xiao-Peng Zhang (Ü ), and Peter Wonka 1Visual Computing Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia 2National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 3School of Software, Tsinghua University, Beijing 100084, China 4Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, U.S.A. E-mail:
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[email protected] Received March 9, 2015; revised April 2, 2015. 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 blue-noise sampling, Poisson-disk sampling, Lloyd relaxation, rendering, remeshing 1 Introduction concentrated spikes in energy. Intuitively, blue-noise sampling generates randomized uniform distributions.