Information Theory tools, which are widely used in fields such as communication, physics, genetics, neuroscience and many others, have emerged as useful transversal tools in the field of visualization. Information Theory Tools for Visualization covers both the basic theoretical concepts behind these tools as well as their use in different visualization applications. Drawing together the work of a number of leading experts in this field, this book offers a useful guide to which problems can be solved with Information Theory tools as well as the means of doing so. Following an introduction to Information Theory, the book enlists five chapters to explore five major aspects of visualization, including theoretical foundation, viewpoint optimization, volume visualization, flow visualization, and information visualization. With the aid of many examples, each chapter provides a comprehensive description of how Information Theory tools can be used to solve visualization problems. Key features, First book solely dedicated to information Theory techniques for visualization, Written by leading experts in the field, Provides comprehensive coverage of the scientific literature on Information Theory tools for visualization, Offers a range of applications of Information Theory in visualization, including volume rendering, streamline seeding, viewpoint selection, summary tree construction, glyph-based visualization, multivariate data exploration, process optimization for visual analytics workflows, and so forth, Intended for graduate students and researchers in the fields of visualization, graphics, and image processing, this book assumes a basic understanding of visualization but also offers a handy sketch to basic concepts. Book jacket.