Scientific Computing

From KBImage

Outline:

The advent of the digital computer brought about the ability to collect, create, store and present more information than previously. It also created a new method of science: scientific computing. Scientific computing is the computer model simulation and calculation of the natural phenomena. It is different from other computing in which all the processes are governed by the law of nature, usually a set of equations. The real nature is complicated. The numeric information from the computational simulation is in vast amounts so that scientists may not be able to see, much less interpret, all the results. Fortunately, computational power of today's computers allows this scientific information to be collected, created, stored and presented in a way useful to the research process. Now computer simulation is one of the three fundamental modes of scientific discovery (Other two modes are experimental investigations and theoretical research). Four graphics and image techniques are often used in scientific information processing and presentation. They are computer graphics, visualization, image processing and computer vision. Computer graphics, as defined in this book, is usually more concerned with the generation of artificial images. Visualization attempts to understand the scientific data by making a visible presentation. Image processing is computer manipulation of images. Computer vision is to extract information from images. The application areas span the range of scales from the atomic and subatomic worlds to the vastness of the universe. It encompasses the study of complicated molecules and the building of complicated machinery. It looks at dynamic systems of living creatures and at the dynamics of whole ecosystems.

Of course there are ways to present scientific information other than visually. Sound (sonification) is increasingly recognized as an important method of information display for special types of data. Actually, any display which can act on our senses, such as haptic (force, texture, temperature, etc ...), can be used to present information.

Graphics and image techniques can be used in some other areas too, like computer games, graphic user interface, graphic arts and photo processing. The difference between scientific methods and others is that whether it is knowledge related. The purpose of scientific visualization is to aid in the understand of scientific information, while an artist's rendering of a concept is for illustration. Game graphics and photo processing are just for their visual appearance of the pictures to a human viewer while scientific graphics and image processing are used not only for improving the visual appearance but also for preparing images for measurement of features and structures present, and for image cognition and computer vision as well.

The Introduction of the book reviews how computer graphics and image techniques have evolved to work with digital numerical analysis methods. Section One contains a detailed review of the concepts and techniques used to generate scientific images, to visualize behavior in 2-D, 3-D and 4-D, as static, interactive or animated imagery, to do image processing and measurement and to extract information from images. Section II presents the use of numerical techniques and computer based methods for the calculation, prediction and simulation in different scientific areas. In the Appendix, the basic Visual Analysis tutorial, basic mathematics and user manual of the graphics and image processing software are included. In the CD-ROM which goes with the book, there are software packages for graphics and image processing and a develop environment for readers to program their own solutions.

The book provides the most comprehensive, authoritative, practical and up-to-date coverage of the field. A unique combination of current concepts and practical applications makes it different from any other books. As a rule, the book provides three parts for each concept, algorithm and techniques presented: first, the review of the theory; second, the software for it; third, the programming environment in which the readers can follow the methods presented and develop their own application solutions. The theories in computer graphics, computer visualization, image processing and computer vision are detailed for easy implementation. There is also a thorough presentation of the scientific applications of these theories and techniques. The following branches of scientific computing are fully reviewed : General Science and Engineering, Geometry-Grid Generation, Computational Physical Science, Geographic Information System, Biological and Medical Imaging. Visual Analysis is used all through the book. A brief tutorial is included in Appendix. This book is a textbook in the theory and practice of graphics and image. It provides a software package and an develop environment for scientific computing . This book is suited for application programmers, users and anyone who want to study graphics and image processing as well.

Contents:

1. Introduction

Section I Graphics and Image Techniques

2. Computer Graphics
1. Introduction
2. Graphics Hardware
3. Geometric Primitives
4. Geometric Modeling Techniques
5. Visual Realism
3. Computer Visualization
1. Graph Plot
2. Still Imagery
3. Animation
4. Surface Rendering
5. Volume Rendering
6. Virtual Reality
4. Image Processing
1. Image Correction and Enhancement
2. Image Filtering
3. Binary Processing
4. Segmentation and Thresholding
5. Image Registration and Fusion
6. Multiscale Analysis - wavelet
7. Image Compression
8. Image Measurement
5. Computer Vision
1. Low-Level image processing and tracking
2. Middle Level Vision - model matching
3. High Level Vision - image understanding

Section II Scientific Applications

6. General Science and Engineering
1. Signal Processing
2. Integration
3. Eigen Systems
4. Linear Systems
5. Nonlinear Systems
6. Ordinal Differential Equations
7. Optimization
8. Correlation Analysis and Forecasting
9. Hypothesis Testing
7. Geometry-Grid Generation
1. Solution Strategy

Finite difference
Finite volume
Finite element

2. Grid Strategy

Structured grid
Unstructured grid
Hybrid grid

3. Generation Process

Computational mapping
Geometry generation
Computational modeling

8. Computational Physical Science
1. Computational Fluid Dynamics
2. Computational Reacting Flow
3. Particle Methods and Plasma Physics
4. Computational Magnetohydrodynamics
5. Computational Electromagnetics
6. Computational Ocean Modeling
7. Astronomical Imaging Processing
8. Astrophysics Process Simulation and Visualization
9. Geographic Information System
10. Biology and Medical Imaging
1. Reconstruction Algorithms
2. 3-D Tomography
3. Multi-Planar Reformating
4. Angiography
5. Virtuoscopy
6. Tracer Kinetic Model