Data Visualization (Hardcover)

Alexandru C. Telea

ISBN 10: 1466585269 / ISBN 13: 9781466585263

Published by Taylor & Francis Inc, Natick, 2014

About this Item

Hardcover. Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration with third-party code, and more. Focusing on those techniques and methods with the broadest applicability across fields, the second edition of Data Visualization: Principles and Practice provides a streamlined introduction to various visualization techniques. The book illustrates a wide variety of applications of data visualizations, illustrating the range of problems that can be tackled by such methods, and emphasizes the strong connections between visualization and related disciplines such as imaging and computer graphics. It covers a wide range of sub-topics in data visualization: data representation; visualization of scalar, vector, tensor, and volumetric data; image processing and domain modeling techniques; and information visualization.See Whats New in the Second Edition: Additional visualization algorithms and techniquesNew examples of combined techniques for diffusion tensor imaging (DTI) visualization, illustrative fiber track rendering, and fiber bundling techniquesAdditional techniques for point-cloud reconstruction Additional advanced image segmentation algorithmsSeveral important software systems and librariesAlgorithmic and software design issues are illustrated throughout by (pseudo)code fragments written in the C++ programming language. Exercises covering the topics discussed in the book, as well as datasets and source code, are also provided as additional online resources. This book explores the study of processing and visually representing data sets. Data visualization is closely related to information graphics, information visualization, scientific visualization, and statistical graphics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9781466585263

Bibliographic Details

• Title: Data Visualization (Hardcover)
• Publisher: Taylor & Francis Inc, Natick
• Publication Date: 2014
• Language: English
• ISBN 10: 1466585269
• ISBN 13: 9781466585263
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: new

About this title

Synopsis

Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration with third-party code, and more.

Focusing on those techniques and methods with the broadest applicability across fields, the second edition of Data Visualization: Principles and Practice provides a streamlined introduction to various visualization techniques. The book illustrates a wide variety of applications of data visualizations, illustrating the range of problems that can be tackled by such methods, and emphasizes the strong connections between visualization and related disciplines such as imaging and computer graphics. It covers a wide range of sub-topics in data visualization: data representation; visualization of scalar, vector, tensor, and volumetric data; image processing and domain modeling techniques; and information visualization.

See What’s New in the Second Edition:

• Additional visualization algorithms and techniques
• New examples of combined techniques for diffusion tensor imaging (DTI) visualization, illustrative fiber track rendering, and fiber bundling techniques
• Additional techniques for point-cloud reconstruction
• Additional advanced image segmentation algorithms
• Several important software systems and libraries

Algorithmic and software design issues are illustrated throughout by (pseudo)code fragments written in the C++ programming language. Exercises covering the topics discussed in the book, as well as datasets and source code, are also provided as additional online resources.

About the Author

Alexandru C. Telea, Professor of Visual Data Analytics at the Department of Information and Computing Sciences, Utrecht University. Former professor of Multiscale Visual Analytics in the Scientific Visualization and Computer Graphics (SVCG) group at the Bernoulli Institute, Faculty of Science and Engineering, University of Groningen.