A Survey of Blue-Noise Sampling and Its Applications

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

doi:10.1007/s11390-015-1535-0

Cited by 60 publications

(28 citation statements)

References 98 publications

(142 reference statements)

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“…Cook proposes Poisson‐disk sampling or jittering on a regular grid as two methods to generate such point sets [Coo86]. The majority of research on blue‐noise sampling deals with the generation of samples at suitable locations, and we refer to Yan et al [YGW∗15] for an extensive survey of sampling methods. The following methods are closely related to our research because they either subsample a given set of points or produce hierarchical representations of three‐dimensional point clouds by generating samples on a mesh.…”

Section: Related Workmentioning

confidence: 99%

“…The subsampling strategy used during the indexing step in section 4.2 is, with some limitations, exchangeable. We implemented and evaluated two approaches, a fast random sampling strategy with a certain level of uniformity as described by Kang et al [KJWX19], and an approximate Poisson‐disk sampling strategy [Coo86; YGW∗15] that enforces a minimum distance between points except between adjacent octree nodes. For each node, the input to the sampling method consists of points in its direct child nodes.…”

Section: Subsamplingmentioning

confidence: 99%

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Fast Out‐of‐Core Octree Generation for Massive Point Clouds

Schütz

Ohrhallinger

Wimmer

2020

Computer Graphics Forum

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Section: Related Workmentioning

confidence: 99%

Section: Subsamplingmentioning

confidence: 99%

Fast Out‐of‐Core Octree Generation for Massive Point Clouds

Schütz

Ohrhallinger

Wimmer

2020

Computer Graphics Forum

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“…This representation resembles stippling [MARI17] and builds on the porosity definition by using the metaphor of clustered grains of rock to encode porosity. In this representation, the grains are represented as decals , and the variation of porosity on the reservoir is encoded by arranging decals on the surface using a sampling strategy based on Poisson sampling [CCS12, YGW*15]. It provides a good strategy to convey trends of the porosity distribution in a smooth way, i.e., there is a smooth transition across cell boundaries.…”

Section: Visualization Designmentioning

confidence: 99%

Illustrative Multivariate Visualization for Geological Modelling

Rocha

Mota

Hamdi

et al. 2018

Computer Graphics Forum

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In this paper, we present a novel illustrative multivariate visualization for geological modelling to assist geologists and reservoir engineers in visualizing multivariate datasets in superimposed representations, in contrast to the single-attribute visualizations supported by commercial software. Our approach extends the use of decals from a single surface to 3D irregular grids, using the layering concept to represent multiple attributes. We also build upon prior work to augment the design and implementation of different geological attributes (namely, rock type, porosity, and permeability). More specifically, we propose a new sampling strategy to generate decals for porosity on the geological grid, a hybrid visualization for permeability which combines 2D decals and 3D ellipsoid glyphs, and a perceptually-based design that allows us to visualize additional attributes (e.g., oil saturation) while avoiding visual interference between layers. Furthermore, our visual design draws from traditional geological illustrations, facilitating the understanding and communication between interdisciplinary teams. An evaluation by domain experts highlights the potential of our approach for geological modelling and interpretation in this complex domain.A. Rocha et al. / Illustrative Multivariate Visualization for Geological Modelling pinch-outs, or when surfaces intersect each other, such as when grid aligned cross-sections are used to explore 3D internal structures-a common strategy adopted by reservoir engineers and geologists.By combining colormaps, decals, decal-maps as well as a 3D glyph-based representation, we represent the following geological data attributes: rock type (categorical data), porosity (scalar data), permeability (tensor data), and oil saturation (scalar data). For porosity representation, we contribute a new importance-sampling strategy to generate decal distributions on the deformed corner point grid. For permeability, we propose a hybrid visualization strategy that combines 2D decals and 3D ellipsoid glyphs. Our perceptually-based design allows us to visualize additional geological attributes such as oil saturation, while avoiding visual interference between attribute layers. Our visual design draws from traditional geological illustrations, facilitating the understanding and communication between interdisciplinary teams. Moreover, we evaluate our technique with domain experts via real walk-through scenarios to highlight the potential of our approach for geological modelling and interpretation in this complex domain. Our main contributions in this work are as follows:

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“…In this section, we only discuss a number of surface sampling algorithms. Extensive surveys of blue noise sampling techniques were presented by Lagae and Dutré [6] and Yan et al [14]. The classic dart-throwing algorithm was first generalized to mesh surfaces by Cline et al [15].…”

Section: Samplingmentioning

confidence: 99%

Analyzing surface sampling patterns using the localized pair correlation function

et al. 2016

Self Cite

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Point distributions with different characteristics have a crucial influence on graphics applications. Various analysis tools have been developed in recent years, mainly for blue noise sampling in Euclidean domains. In this paper, we present a new method to analyze the properties of general sampling patterns that are distributed on mesh surfaces. The core idea is to generalize to surfaces the pair correlation function (PCF) which has successfully been employed in sampling pattern analysis and synthesis in 2D and 3D. Experimental results demonstrate that the proposed approach can reveal correlations of point sets generated by a wide range of sampling algorithms. An acceleration technique is also suggested to improve the performance of the PCF.

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A Survey of Blue-Noise Sampling and Its Applications

Cited by 60 publications

References 98 publications

Fast Out‐of‐Core Octree Generation for Massive Point Clouds

Fast Out‐of‐Core Octree Generation for Massive Point Clouds

Illustrative Multivariate Visualization for Geological Modelling

Analyzing surface sampling patterns using the localized pair correlation function

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