Scientific visualization has become an important tool for visual analysis in many scientific, engineering, and medical disciplines.
This book focuses on efficient visualization techniques, which are the prerequisite for the interactive exploration of complex data sets. High performance is primarily achieved by devising algorithms for the fast graphics processing units (GPUs) of modern graphics hardware. Other aspects discussed in the book include parallelization on cluster computers with several GPUs, adaptive rendering methods, multi-resolution models, and non-photorealistic rendering techniques for visualization. Covering both the theoretical foundations and practical implementations of algorithms, this book provides the reader with a basis to understand and reproduce modern GPU-based visualization approaches.
Table of Content
Contents 1 Introduction 1.1 Visualization Pipeline and Classification of Visualization Methods 1.2 GPU Rendering Pipeline 1.3 Methods and Goals 2 Visualization of 3D Scalar Fields 2.1 Optical Model for Volume Rendering 2.2 Volume Rendering Pipeline 2.3 Volume Rendering Approaches 2.4 Maintaining Constant Frame Rates in 3D Texture-Based Volume Rendering 2.5 Volume Clipping 2.6 Hierarchical Volume Visualization on GPU Clusters 2.7 Summary 3 Vector Field Visualization 3.1 Basics of Particle Tracing 3.2 Classification and Overview of Flow Visualization Methods 3.3 Semi-Lagrangian Noise and Dye Advection on Cartesian Domains 3.4 Dye Advection Based on Level-Sets 3.5 Flow Visualization on Curved Surfaces 3.6 Spacetime Framework for Time-Dependent Vector Fields 3.7 Summary 4 Perception-Oriented and Non-Photorealistic Rendering 4.1 Previous Work 4.2 Colorand the Perceptionof Motion 4.3 Color-Based Depth-Cueing 4.4 Non-Photorealistic Rendering of Depth Structures via Continuous Tone-Shading 4.5 Non-Photorealistic Halftoning 4.6 Summary 5 Conclusion References Color Plates Index
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