Visualization Handbook
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Table of contents
- Contentsv
- Contributorsviii
- Prefacexiv
- Acknowledgmentsxviii
- PART I Introduction1
- 1 Overview of Visualization3
- 1.1 Introduction3
- 1.2 Scalar Algorithms5
- 1.3 Vector Algorithms13
- 1.4 Tensor Algorithms20
- 1.5 Modeling Algorithms22
- 1.6 Bibliographic Notes33
- PART II Scalar Field Visualization: Isosurfaces37
- 2 Accelerated Isosurface Extraction Approaches39
- 2.1 Introduction39
- 2.2 Isosurface Extraction Approaches39
- 2.3 The Span Space41
- 2.4 Near-Optimal Isosurface Extraction42
- 2.5 View-Dependent Isosurface Extraction48
- 2.6 Summary54
- 3 Time-Dependent Isosurface Extraction57
- 3.1 Space-Efficient Search Data Structure57
- 3.2 Extracting Isosurfaces in Four64
- 4 Optimal Isosurface Extraction69
- 4.1 Introduction69
- 4.2 Selecting Cells Through Interval Trees71
- 4.3 Extraction of Isosurfaces from Structured and Unstructured Grids75
- 4.4 Assessment80
- 5 Isosurface Extraction Using Extrema Graphs83
- 5.1 Introduction83
- 5.2 Isosurface Propagation84
- 5.3 Isosurface Generation Using an Extrema Graph87
- 5.4 Isosurface Generation Using an Extrema Skeleton90
- 5.5 Skeleton Generation for the Extraction of Numerical Features93
- 5.6 Conclusion94
- 6 Isosurfaces and Level-Sets97
- 6.1 Introduction97
- 6.2 Surface Normals99
- 6.3 Second-Order Structure99
- 6.4 Deformable Surfaces100
- 6.5 Deformation: The Level-Set Approach101
- 6.6 Numerical Methods103
- 6.7 Applications111
- 6.8 Summary121
- PART III Scalar Field Visualization: Volume Rendering125
- 7 Overview of Volume Rendering127
- 7.1 Introduction127
- 7.2 Volumetric Data127
- 7.3 Rendering via Geometric Primitives128
- 7.4 Direct Volume Rendering: Prelude129
- 7.5 Volumetric Function Interpolation130
- 7.6 Volume Rendering Techniques133
- 7.7 Acceleration Techniques144
- 7.8 Classification and Transfer Functions149
- 7.9 Volumetric Global Illumination152
- 7.10 Rendering on Parallel Architectures154
- 7.11 Special-Purpose Rendering Hardware155
- 7.12 General-Purpose Rendering Hardware157
- 7.13 Irregular Grids158
- 7.14 Time-Varying and High-Dimensional Data160
- 7.15 Multichannel and Multimodal Data162
- 7.16 Nonphotorealistic Volume Rendering163
- 8 Volume Rendering Using Splatting175
- 8.1 The Theory175
- 8.2 Image-Aligned Sheet-Based Splatting178
- 8.3 Splatting with Shadows180
- 8.4 Future Work187
- 9 Multidimensional Transfer Functions for Volume Rendering189
- 9.1 Introduction189
- 9.2 Previous Work190
- 9.3 Multidimensional Transfer Functions191
- 9.4 Interaction and Tools196
- 9.5 Rendering and Hardware201
- 9.6 Discussion206
- 10 Pre-Integrated Volume Rendering211
- 10.1 Introduction to Pre-Integrated Volume Rendering211
- 10.2 Pre-Integrated Volume Rendering Algorithms215
- 10.3 Accelerated Pre-Integration219
- 10.4 Pre-Integrated Rendering Techniques222
- 10.5 Open Problems226
- 11 Hardware-Accelerated Volume Rendering229
- 11.1 Introduction229
- 11.2 Volume Rendering Basics229
- 11.3 The Volume Rendering Pipeline233
- 11.4 Advanced Techniques237
- 11.5 Ray-Casting239
- 11.6 Texture Slicing241
- 11.7 Shear-Warp Rendering245
- 11.8 Splatting250
- 11.9 Conclusions253
- PART IV Vector Field Visualization259
- 12 Overview of Flow Visualization261
- 12.1 Introduction261
- 12.2 Mathematical Description of a Vector Field261
- 12.3 Particle Tracing in Time-Dependent Flow Fields262
- 12.4 Classification of Visualization Approaches263
- 12.5 Point-Based Direct Flow Visualization263
- 12.6 Sparse Representations for Particle-Tracing Techniques265
- 12.7 Dense Representations for Particle-Tracing Methods268
- 12.8 Feature-Based Visualization Approaches271
- 13 Flow Textures: High-Resolution Flow Visualization279
- 13.1 Introduction279
- 13.2 Underlying Model281
- 13.3 Implementing the Dense Set of Particles Model285
- 13.4 GPU-Based Implementation289
- 13.5 Conclusions292
- 14 Detection and Visualization of Vortices295
- 14.1 Introduction295
- 14.2 Taxonomy296
- 14.3 Vortex-Detection Algorithms297
- 14.4 Swirling Flow Verification304
- 14.5 Visualization of Vortices306
- 14.6 Conclusion307
- PART V Tensor Field Visualization311
- 15 Oriented Tensor Reconstruction313
- 15.1 Introduction313
- 15.2 Method313
- 15.3 Discussion321
- 15.4 Conclusions324
- 16 Diffusion Tensor MRI Visualization327
- 16.1 Introduction327
- 16.2 Diffusion Tensor Imaging327
- 16.3 Approaches to Visualizing DTI Datasets329
- 16.4 Open Issues337
- 16.5 Summary338
- 17 Topological Methods for Flow Visualization341
- 17.1 Introduction341
- 17.2 Vector Field Topology342
- 17.3 Tensor-Field Topology346
- 17.4 Topological Visualization of Vector and Tensor Fields350
- PART VI Geometric Modeling for Visualization357
- 18 3D Mesh Compression359
- 18.1 Introduction359
- 18.2 Background and Terminology359
- 18.3 Corner Table Representation360
- 18.4 Geometry Compression361
- 18.5 Connectivity Compression362
- 18.6 Retiling373
- 18.7 Conclusion376
- 19 Variational Modeling Methods for Visualization381
- 19.1 Introduction381
- 19.2 Fundamentals from Differential Geometry381
- 19.3 Variational Surface Modeling382
- 19.4 Curve and Surface Interrogation385
- 19.5 Geodesics386
- 19.6 Curvature Lines390
- 19.7 Simulation-Based Solid Modeling391
- 20 Model Simplification393
- 20.1 Introduction393
- 20.2 Model Domains394
- 20.3 Types of Hierarchies396
- 20.4 Building Hierarchies399
- 20.5 Managing Hierarchies403
- 20.6 Conclusion407
- PART VII Virtual Environments for Visualization411
- 21 Direct Manipulation in Virtual Reality413
- 21.1 Introduction413
- 21.2 Basics of Direct Manipulation416
- 21.3 System Architecture Issues421
- 21.4 Distributed Implementation425
- 21.5 Time-Critical Techniques427
- 21.6 Conclusions430
- 22 The Visual Haptic Workbench431
- 22.1 Introduction431
- 22.2 The Visual Haptic Workbench431
- 22.3 Haptic Rendering Techniques for Scientific Visualization435
- 22.4 Data Exploration with Haptic Constraints436
- 22.5 Examples441
- 22.6 Summary and Future Work443
- 23 Virtual Geographic Information Systems449
- 23.1 Introduction449
- 23.2 Key Work in the Development of Virtual GIS450
- 23.3 Global, Comprehensive Organization of Geospatial Data452
- 23.4 Multiresolution Models457
- 23.5 Interaction and Display462
- 23.6 Some Applications469
- 23.7 Conclusions and Future Work473
- 24 Visualization Using Virtual Reality479
- 24.1 Introduction479
- 24.2 A Visualization Sampler481
- 24.3 Research Challenges486
- PART VIII Large-Scale Data Visualization491
- 25 Desktop Delivery: Access to Large Datasets493
- 25.1 Introduction493
- 25.2 Background494
- 25.3 Framing the Problem497
- 26 Techniques for Visualizing Time-Varying Volume Data511
- 26.1 Introduction511
- 26.2 Characteristics of Time-Varying Volume Data511
- 26.3 Encoding513
- 26.4 Interactive Hardware-Accelerated Rendering514
- 26.5 Parallel Pipelined Rendering522
- 26.6 Conclusions530
- 27 Large-Scale Data Visualization and Rendering: A Problem-Driven Approach533
- 27.1 Introduction533
- 27.2 Hybrid Systems544
- 27.3 Rendering547
- 27.4 Conclusions549
- 28 Issues and Architectures in Large-Scale Data Visualization551
- 28.1 Introduction551
- 28.2 Characterizing the Problem551
- 28.3 An End-to-End Architecture for Large Data Exploration555
- 28.4 Commodity-Based Scalable Visualization Systems557
- 28.5 Interoperable Component-Based Solutions-Is There Any Hope?561
- 28.6 The ASCI/VIEWS Program563
- 28.7 Conclusion566
- 29 Consuming Network Bandwidth with Visapult569
- 29.1 Introduction569
- 29.2 Visapult Architecture569
- 29.3 Reading Data Over the Network Using TCP571
- 29.4 The Bandwidth Challenges and Results573
- 29.4.2 SC 2001 Bandwidth Challenge576
- 29.5 Lessons Learned582
- 29.6 Future Directions for High-Performance Remote and Distributed Visualization586
- 29.7 Conclusion588
- PART IX Visualization Software and Frameworks591
- 30 The Visualization Toolkit593
- 30.1 Introduction593
- 30.2 Overview595
- 30.3 Methods in Large-Data Visualization606
- 30.4 VTK in Application610
- 31 Visualization in the SCIRun Problem-Solving Environment615
- 31.1 Introduction to SCIRun615
- 31.2 SCIRun Visualization Tools618
- 31.3 Remote and Collaborative Visualization619
- 31.4 SCIRun Applications621
- 31.5 Getting Started in SCIRun630
- 32 NAG’s IRIS Explorer633
- 32.1 Introduction633
- 32.2 Getting Started with IRIS Explorer635
- 32.3 Working with IRIS Explorer638
- 32.4 Underlying Software in IRIS Explorer641
- 32.5 Some Applications of IRIS Explorer644
- 32.6 Moving IRIS Explorer to the Grid650
- 32.7 Conclusions652
- 33 AVS and AVS/Express655
- 33.1 Introduction655
- 33.2 Design Principles for AVS and AVS/Express656
- 33.3 AVS/Express Quick User Overview657
- 33.4 AVS/Express Architecture659
- 33.5 The Field Data Type665
- 33.6 The Integrated Rendering Subsystem667
- 33.7 Example of a New Module Derivation669
- 33.8 Conclusions671
- 34 Vis5D, Cave5D, and VisAD673
- 34.1 Introduction673
- 34.2 Vis5D673
- 34.3 Cave5D677
- 34.4 VisAD678
- 35 Visualization with AVS689
- 35.1 Introduction689
- 35.2 Meterological Visualization: Global and Regional Climate Modeling689
- 35.3 Earth Science Visualization: What Is Inside Stars and Planets692
- 35.4 Flow Visualization: Extracting and Visualizing Vortex Features697
- 35.5 Visualizing Engineering Data: Stresses and Deformations of Architectural Structures701
- 35.6 Medical Visualization: Endovascular Surgical Planning Tool704
- 35.7 Archaeological Visualization: Uncovering the Past708
- 35.8 Molecular Visualization: Seeing 3D Chemical Structure711
- 35.9 Visualization with AVS: Conclusion715
- 36 ParaView: An End-User Tool for Large-Data Visualization717
- 36.1 Introduction717
- 36.2 Related Work718
- 36.3 Design719
- 36.4 Results728
- 36.5 Conclusions730
- 37 The Insight Toolkit: An Open-Source Initiative in Data Segmentation and Registration733
- 37.1 Introduction733
- 37.2 Background733
- 37.3 An ITK Example734
- 37.4 Background and History of the Toolkit735
- 37.5 Design Principles736
- 37.6 Software Engineering Infrastructure738
- 37.7 The Elements of ITK741
- 37.8 More on ITK746
- 37.9 Conclusion748
- 38 amira: A Highly Interactive System for Visual Data Analysis749
- 38.1 Introduction749
- 38.2 General Concepts750
- 38.3 Features and Applications754
- 38.4 amiraVR and Other Extensions761
- 38.5 Summary765
- PART X Perceptual Issues in Visualization769
- 39 Extending Visualization to Perceptualization: The Importance of Perception in Effective Communica771
- 39.1 Introduction771
- 39.2 Overview of Human Perception772
- 39.3 Examples of Perceptualization Research773
- 39.4 Conclusions778
- 40 Art and Science in Visualization781
- 40.1 Introduction781
- 40.2 Case Study 1: Effectively Portraying Dense Collections of Overlapping Lines784
- 40.3 Case Study 2: Using Feature Lines to Emphasize the Essential 3D Structure of a Form786
- 40.4 Case Study 3: Clarifying the 3D Shapes, and Relative Positions in Depth, of Arbitrary Smoothly790
- 40.5 Conclusions802
- 41 Exploiting Human Visual Perception in Visualization807
- 41.1 Introduction 41.2 Visualizing the Past807
- 41.3 Visual Perception808
- 41.4 Conclusions813
- PART XI Selected Topics and Applications817
- 42 Scalable Network Visualization819
- 42.1 Introduction819
- 42.2 Network Background819
- 42.3 Visual Metaphors for Networks821
- 42.4 Visual Scalability823
- 42.5 Examples824
- 42.6 Discussion827
- 43 Visual Data-Mining Techniques831
- 43.1 Introduction831
- 43.2 Methodology of Visual Data Mining832
- 43.3 Association Rules835
- 43.4 Classification837
- 43.5 Clustering838
- 43.6 Text841
- 43.7 Conclusion842
- 44 Visualization in Weather and Climate Research845
- 44.1 A Brief History845
- 44.2 Weather and Climate Research847
- 44.3 Data and Grids848
- 44.4 Visualization and Analysis Tools850
- 44.5 Visualization Case Studies in Weather and Climate Research851
- 44.6 Visualization Challenges and Futures865
- 44.7 Summary870
- 45 Painting and Visualization873
- 45.1 Introduction873
- 45.2 Mimicking Artists: Strokes, Design, Critiques, and Sketching874
- 45.3 Historical Perspective: The Connections Between Art and Science882
- 45.4 Open Issues886
- 45.5 Summary889
- 46 Visualization and Natural Control Systems for Microscopy893
- 46.1 Introduction893
- 46.2 nanoManipulator896
- 46.3 NIMS: nM + SEM902
- 46.3.3 Results903
- 46.3.4 Lessons Learned904
- 46.4 3DFM904
- 46.5 AIMS: TEM + MEMS907
- 46.6 TeleMicroscopy909
- 46.7 Conclusions913
- 47 Visualization for Computational Accelerator Physics919
- 47.1 Introduction919
- 47.2 Visualizing Beam Dynamics Simulations919
- 47.3 Visualizing Electromagnetic Field Data925
- index937
The Visualization Handbook provides an overview of the field of visualization by presenting the basic concepts, providing a snapshot of current visualization software systems, and examining research topics that are advancing the field.
This text is intended for a broad audience, including not only the visualization expert seeking advanced methods to solve a particular problem, but also the novice looking for general background information on visualization topics. The largest collection of state-of-the-art visualization research yet gathered in a single volume, this book includes articles by a “who’s who of international scientific visualization researchers covering every aspect of the discipline, including:
· Virtual environments for visualization
· Basic visualization algorithms
· Large-scale data visualization
· Scalar data isosurface methods
· Visualization software and frameworks
· Scalar data volume rendering
· Perceptual issues in visualization
· Various application topics, including information visualization.
* Edited by two of the best known people in the world on the subject; chapter authors are authoritative experts in their own fields;
* Covers a wide range of topics, in 47 chapters, representing the state-of-the-art of scientific visualization.
This text is intended for a broad audience, including not only the visualization expert seeking advanced methods to solve a particular problem, but also the novice looking for general background information on visualization topics. The largest collection of state-of-the-art visualization research yet gathered in a single volume, this book includes articles by a “who’s who of international scientific visualization researchers covering every aspect of the discipline, including:
· Virtual environments for visualization
· Basic visualization algorithms
· Large-scale data visualization
· Scalar data isosurface methods
· Visualization software and frameworks
· Scalar data volume rendering
· Perceptual issues in visualization
· Various application topics, including information visualization.
* Edited by two of the best known people in the world on the subject; chapter authors are authoritative experts in their own fields;
* Covers a wide range of topics, in 47 chapters, representing the state-of-the-art of scientific visualization.