Focus on Scientific Visualization

One of the important issues of Scientific Visualization is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes and simulations involving voluminous data sets across diverse scientific disciplines. This book presents the state-of-the-art in visualization techniques both as an overview for the inquiring scientist, and as a solid platform from which developers may extend existing techniques or devise new ones to meet the specific needs of their problems. A secondary goal in crafting this volume has been to provide a vehicle for teaching of state-of-the-art techniques in scientific visualization. The first part of the book covers the application areas fluid flow visualization in medicine, and environmental protection. The second set of chapters explain fundamentals of scientific visualization. It comprises contributions on data structuring and data administration, data modeling, and rendering. A final section is devoted to auditory representation of scientific data.

Contenu

Fluid Flow Visualization.- 1 Introduction.- 1.1 Purposes and Problems of Flow Visualization.- 1.2 Overview.- 2 Experimental Flow Visualization.- 2.1 Addition of Foreign Material.- 2.2 Optical Techniques.- 2.3 Addition of Heat and Energy.- 3 Computer Graphics Flow Visualization.- 3.1 The Flow Visualization Process.- 3.2 Flow Visualization Mappings.- 3.3 Data Preparation.- 3.3.1 Filtering.- 3.3.2 Data Selection.- 3.3.3 Domain Transformations.- 3.3.4 Interpolation.- 3.3.5 Point Location.- 3.3.6 Computing Derived Scalar Quantities.- 3.3.7 Computing Particle Path Lines.- 3.3.8 Contour Lines and Surfaces.- 3.4 Flow Field Topology.- 3.4.1 Critical points.- 3.4.2 Integral Curves and Surfaces.- 4 Presentation Techniques.- 4.1 Human Perception and Depth Cues.- 4.2 Basic Rendering Techniques.- 4.2.1 Arrows.- 4.2.2 Curves.- 4.2.3 Surfaces.- 4.2.4 Particles.- 4.2.5 Environment Geometry.- 4.2.6 Volume Rendering.- 4.3 Special Rendering Techniques.- 4.3.1 Animation.- 4.3.2 Aliasing and Anti-Aliasing.- 4.3.3 Texture Synthesis and Texture Mapping.- 4.3.4 Hybrid Rendering.- 4.3.5 Advanced Particle Rendering.- 5 Conclusions and Research Directions.- References.- Volume Visualization in Medicine: Techniques and Applications.- 1 Introduction.- 1.1 Objectives.- 1.2 Related Fields.- 2 Imaging Modalities.- 3 Methods.- 3.1 Overview.- 3.2 Preprocessing.- 3.2.1 Data Conversion.- 3.2.2 Filtering.- 3.2.3 Interpolation.- 3.2.4 Data Structures.- 3.3 Object Definition.- 3.3.1 Segmentation.- 3.3.2 Interpretation.- 3.4 Surface-Based Rendering.- 3.4.1 Surface Reconstruction from Contours.- 3.4.2 Surface Reconstruction from Volumes.- 3.4.3 Shading.- 3.5 Voxel-Based Rendering.- 3.5.1 Projection Techniques.- 3.5.2 Surfaces.- 3.5.3 Cut Planes.- 3.5.4 Integral and Maximum Intensity Projection.- 3.5.5 Volume Rendering.- 3.6 Advanced Segmentation Methods.- 3.6.1 Point-Based Segmentation.- 3.6.2 Edge-Based Segmentation.- 3.6.3 Region-Based Segmentation.- 3.7 Multimodality Matching.- 3.8 Manipulation.- 3.9 Image Fidelity.- 3.10 Implementation Aspects.- 4 Applications.- 5 Conclusions.- References.- Application of Visualization in Environmental Protection.- 1 Introduction.- 2 Applications of Software Systems in Environmental Protection.- 2.1 Monitoring and Control Systems.- 2.2 Information Systems.- 2.3 Evaluation and Interpretation Systems.- 2.4 Decision Support Systems.- 2.5 Environmental Information Systems.- 3 Requirements of Visualization Systems.- 4 Methods and Applications.- 4.1 Data Analysis and Control in Monitoring Systems.- 4.2 Information Systems.- 4.3 Scattered Data Methods.- 4.4 Particle Flow Visualization and Animation.- 4.5 Groundwater Protection and Finite Element Methods.- 4.6 Intelligent User Interfaces in Process Control.- 5 Conclusions.- References.- Data Structures in Scientific Visualization.- 1 Introduction.- 2 Computer Based Problem Handling.- 2.1 The Modeling Phase.- 2.2 The Simulation Phase.- 2.3 The Evaluation Phase.- 3 Data Types of Dependent Variables.- 3.1 Basic Data Types.- 3.2 Dimensionality of Dependent Variables.- 3.2.1 Scalar Fields.- 3.2.2 Vector Fields.- 3.2.3 Tensor Fields.- 4 Coordinate Systems.- 5 Connectivity.- 5.1 Cartesian Grids.- 5.2 Uniform Grids.- 5.3 Rectilinear Grids.- 5.4 Regulär Grids.- 5.5 Block-Structured Grids.- 5.6 Irregulär Grids.- 5.7 Hybrid Grids.- 5.8 Scattered Locations.- 6 Zone Data.- 7 Auxiliary Information.- 8 Relationship between Data Sets.- 9 Consideration of Time.- 9.1 Handling of Time Information.- 9.1.1 Fixed Time Step Size.- 9.1.2 Variable Time Step Size.- 9.2 Time Dependence of Data.- 9.3 Time Dependence of Grids.- 9.4 Time Dependence of Connectivity.- 9.5 Different Time Steps in Separate Parts.- 10 Data Structures in Different Software Packages.- 10.1 The Irregular Grid Approach.- 10.2 Differentiated Data Structure Approach.- 11 Application Package Independent Data Access Software.- 12 Conclusions.- References.- A Visualization-Based Model for a Scientific Database System.- 1 Introduction.- 2 A Paradigm for Interdisciplinary Scientific Research.- 3 Nature of Scientific Data.- 3.1 Lattice-Oriented Data.- 3.2 Relationships Among Data.- 3.3 Data and Models of Data.- 3.4 Meaning of Updates.- 3.5 Related Database Developments.- 4 Nature of Scientific Data Visualization.- 4.1 Traditional Visualization Techniques.- 4.2 Multi-Dimensional Data Visualization.- 4.3 Systems for Scientific Data Visualization.- 5 Toward a Target Scientific Database System.- 5.1 Terminology.- 5.2 Metadata.- 5.3 Schema Model.- 5.4 Schema Evolution.- 5.5 Bridge to Knowledge Based Systems Technology.- 5.6 Project Overview.- 6 Conclusion.- References.- Volume Synthesis Principles.- 1 Background.- 2 Motivation.- 3 Voxelization Algorithms.- 4 Discrete Ray Tracing.- 5 Concluding Note.- References.- Surface Interpolation from Cross Sections.- 1 Introduction.- 2 Topological Reconstruction.- 2.1 Assignment Graphs and Nesting Trees.- 2.2 Enumeration of Assignment Graphs.- 2.3 Similarity of Contours.- 2.4 Mutual Location of Contours.- 3 Geometrie Reconstruction.- 4 Triangulated Surfaces.- 4.1 Point Reduction.- 4.2 Cylindric Triangulation.- 4.3 Saddle Point Triangulation.- 4.4 Extremal Points.- 4.5 Penetrations.- 4.6 Quality of Triangulations.- 4.6.1 Measure Criteria.- 4.6.2 Shape Criteria and Deformation.- 4.7 Intermediate Layers.- 5 Pyramidal Extrapolation.- 6 Smooth Surface Interpolation.- 7 Volume Oriented Reconstruction.- 8 Interpolation by Spatial Delaunay Triangulations.- 9 Reconstruction with Spatial Grids.- 10 Acquisition of Data.- 11 Interaction.- 11.1 Segmentation.- 11.2 Topological Assignment.- 11.3 Deformation.- 11.4 Triangulation.- 12 Concluding Remarks.- References.- Modeling and Visualizing Volumetrie and Surface-on-Surface Data.- 1 Introduction.- 2 Data.- 2.1 Pressure on a Wing Example.- 2.2 CAT Scan Data Example.- 2.3 Precipitation on Earth Data Example.- 2.4 Temperature Analysis Data Example.- 2.5 Flame Data Example.- 2.6 Well Log Data Example.- 2.7 Brain Data Example.- 2.8 Spatial Sound Data Example.- 2.9 Summary of Data Examples.- 3 Visualization Methods.- 3.1 Techniques for Visualizing Volumetrie Models.- 3.1.1 Domain Decomposition Methods.- 3.1.2 Slice Methods.- 3.1.3 Contour Methods.- 3.1.4 Volume Rendering (Ray Casting) Methods.- 3.1.5 Volume Interrogation Techniques.- 3.2 Techniques for Visualizing Surface-on-Surface Models.- 4 Modeling Methods.- 4.1 Distance Function Approach.- 4.1.1 Volumetrie Data.- 4.1.2 Surface-on-Surface Data.- 4.2 Piecewise Hermite Approach.- 4.2.1 Surface-on-Surface Data.- 4.2.2 Volumetric Data.- References.- Curve and Surface Interrogation.- 1 Introduction.- 2 Reflection Line Method.- 3 Isophotes.- 4 Orthotomics.- 5 Polarity Method.- 6 Focal Surfaces.- References.- Sorting for Polyhedron Compositing.- 1 Polyhedron Compositing.- 2 A General Sorting Algorithm.- 3 Adaptive Mesh Refinement.- 4 Sorting for the AMR Method.- 5 Interpolation and Contour Surfaces.- 6 Sorting for Cloud V…