9783540250760-354025076X-Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration (Mathematics and Visualization)

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

ISBN-13: 9783540250760
ISBN-10: 354025076X
Edition: 2009
Author: Bernd Hamann, Robert D. Russell, Torsten Möller
Publication date: 2009
Publisher: Springer
Format: Hardcover 360 pages
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ISBN-13: 9783540250760
ISBN-10: 354025076X
Edition: 2009
Author: Bernd Hamann, Robert D. Russell, Torsten Möller
Publication date: 2009
Publisher: Springer
Format: Hardcover 360 pages

Summary

Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration (Mathematics and Visualization) (ISBN-13: 9783540250760 and ISBN-10: 354025076X), written by authors Bernd Hamann, Robert D. Russell, Torsten Möller, was published by Springer in 2009. With an overall rating of 4.4 stars, it's a notable title among other Computer Science books. You can easily purchase or rent Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration (Mathematics and Visualization) (Hardcover) from BooksRun, along with many other new and used Computer Science books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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.

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