Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration (eBook)

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2009 | 2009
X, 350 Seiten
Springer Berlin (Verlag)
978-3-540-49926-8 (ISBN)

Lese- und Medienproben

Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration -
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The goal of visualization is the accurate, interactive, and intuitive presentation of data. Complex numerical simulations, high-resolution imaging devices and incre- ingly common environment-embedded sensors are the primary generators of m- sive data sets. Being able to derive scienti?c insight from data increasingly depends on having mathematical and perceptual models to provide the necessary foundation for effective data analysis and comprehension. The peer-reviewed state-of-the-art research papers included in this book focus on continuous data models, such as is common in medical imaging or computational modeling. From the viewpoint of a visualization scientist, we typically collaborate with an application scientist or engineer who needs to visually explore or study an object which is given by a set of sample points, which originally may or may not have been connected by a mesh. At some point, one generally employs low-order piecewise polynomial approximationsof an object, using one or several dependent functions. In order to have an understanding of a higher-dimensional geometrical 'object' or function, ef?cient algorithms supporting real-time analysis and manipulation (- tation, zooming) are needed. Often, the data represents 3D or even time-varying 3D phenomena (such as medical data), and the access to different layers (slices) and structures (the underlying topology) comprising such data is needed.

Preface 5
Contents 8
Maximizing Adaptivity in Hierarchical Topological Models Using Cancellation Trees 10
1 Introduction 10
2 Morse–Smale Complex 12
3 Cancellation Forest 14
4 Hierarchy 17
5 Results 21
6 Conclusions and Future Research 26
References 26
The Toporrery: Computation and Presentation of Multiresolution Topology 28
1 Introduction 28
2 Multiresolution Contour Trees 31
3 Hierarchical Morse Functions 36
4 Multiresolution Contour Trees 39
5 Output Sensitive Visualization 44
6 Conclusions 47
Isocontour Based Visualization of Time-Varying Scalar Fields 50
1 Introduction 50
2 Isocontour Extraction 52
3 Topological Structures for Supporting Visualization 57
4 Conclusions 72
References 74
DeBruijn Counting for Visualization Algorithms 78
1 Introduction 78
2 History and Literature 80
3 Permuting the Colors: The Power Group 83
4 Summary 96
References 96
Topological Methods for Visualizing Vortical Flows 98
1 Introduction 98
2 Related Work 100
3 Theoretical Aspects of (Parametric) Topology 100
4 Topology Tracking 104
5 Planar Topology Tracking for Volume Exploration 109
6 Results 111
7 Conclusion 115
References 116
Stability and Computation of Medial Axes: A State-of-the-Art Report 117
1 Introduction 117
2 Medial Axis and Skeleton 118
3 Finiteness Properties 119
4 Homotopy Equivalence 120
5 Instability and Semi-continuity 121
6 Stability Under C2-Perturbations 122
7 Exact Computation of Medial Axes 122
8 Approximation Paradigm for Medial Axes 123
9 Punctured Euclidean Spaces 124
10 Voronoi Graph and Medial Axis 124
11 Pruning in the Presence of Noise 126
12 Stability of the .-Medial Axis 128
13 What Now? 129
References 131
Local Geodesic Parametrization: An Ant’s Perspective 134
1 Introduction 134
2 The Algorithm 136
3 Implementation 139
4 Sample Application 142
5 Conclusion and Future Work 143
References 144
Tensor-Fields Visualization Using a Fabric-like Texture Applied to Arbitrary Two-dimensional Surfaces 145
1 Introduction 145
2 Related Work 146
3 Mathematical Background and Notation 147
4 MethodOverview 148
5 Metric Definition 149
6 Surface Definition and Tensor Projection 150
7 Texture Generation 151
8 Results and Conclusions 157
References 160
Flow Visualization via Partial Differential Equations 162
1 Introduction 162
2 Review of Texture Based Flow Visualization 164
3 A Brief Introduction to Scale Space Methods in Image Processing 166
4 A Flow Aligned Differential Operator 168
5 Anisotropic Diffusion for Stationary Flow 168
6 Transport and Diffusion for Non-stationary Flow Fields 174
7 Continuous Clustering via Anisotropic Phase Separation 178
8 Remarks on the Finite Element Implementation 183
9 Clustering Based on Hierarchical Decomposition of a Differential Operator 184
10 Conclusions 191
References 192
Iterative Twofold Line Integral Convolution for Texture-Based Vector Field Visualization 195
1 Introduction 195
2 Previous Work 196
3 Continuous Twofold Convolution Along Straightened Lines 197
4 Discretization and Sampling 200
5 Extended Scenarios 202
6 Discussion of Costs and Quality 204
7 Implementation and Results 205
8 Conclusion 211
References 214
Constructing 3D Elliptical Gaussians for Irregular Data 216
1 Introduction 216
2 Previous Work 218
3 Creating 3D Elliptical Gaussian 219
4 Evaluation 223
5 Rendering 224
6 Implementation and Results 224
7 Conclusion and Future Work 227
References 228
From Sphere Packing to the Theory of Optimal Lattice Sampling 229
1 Introduction 229
2 Multidimensional Sampling Theory 230
3 The Optimal Lattice Sampling 235
4 The BCC Lattice 236
5 Reconstruction Filters 238
6 Implementation 245
7 Results and Discussion 247
8 Conclusion 253
9 Future Research 254
References 256
Reducing Interpolation Artifacts by Globally Fairing Contours 258
1 Introduction 258
2 Related Work 259
3 Fairing Contours of a Scalar Field 260
4 Numerical Examples 266
5 Conclusions and Future Work 269
References 270
Time- and Space-Efficient Error Calculation for Multiresolution Direct Volume Rendering 271
1 Introduction 271
2 Previous Work 272
3 Error Estimation 274
4 Multiresolution Representation 279
5 Rendering 279
6 Results and Discussion 280
7 Conclusions and Future Work 282
References 283
Massive Data Visualization: A Survey 284
1 Introduction 284
2 Driving Problems 285
3 How Do We Explore Massive Data? 287
4 Simplification Methods 288
5 Multiresolution Methods 290
6 External Memory Methods 292
7 Visual Scalability 294
8 Conclusions 296
References 296
Compression and Occlusion Culling for Fast Isosurface Extraction from Massive Datasets 302
1 Introduction 302
2 Related Work 304
3 Mesh Refinement and Preprocessing 306
4 Data Compression 308
5 Occlusion Culling 311
6 Results 313
7 Conclusions and Future Work 318
References 319
Volume Visualization of Multiple Alignment of Large Genomic DNA 323
1 Introduction 323
2 Our Approach 326
3 Implementation 330
4 Results 332
5 Conclusions 338
References 338
Model-Based Visualization: Computing Perceptually Optimal Visualizations 341
1 Introduction 341
2 Approach 342
3 Discussion 346
References 348

Erscheint lt. Verlag 12.6.2009
Reihe/Serie Mathematics and Visualization
Zusatzinfo X, 350 p. 183 illus., 134 illus. in color.
Verlagsort Berlin
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Grafik / Design
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Technik
Schlagworte 3D • algorithms • Alignment • Computer • Computer Graphics • massive data exploration • Mathematical Modeling • Modeling • PDE methods • Rendering • Sets • stability • Topology • Visualization
ISBN-10 3-540-49926-1 / 3540499261
ISBN-13 978-3-540-49926-8 / 9783540499268
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