Foundations of Multidimensional and Metric Data Structures provides a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets.
The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures. Each section includes a large number of exercises and solutions to self-test and confirm the reader's understanding and suggest future directions.
The book is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS), game programming, image processing, pattern recognition, solid modeling, similarity retrieval, and VLSI design.
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The field of multidimensional data structures is large and growing very quickly. Here, for the first time, is a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets.
The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures. Along with the hundreds of worked exercises and hundreds of illustrations, the result is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS), game programming, image processing, pattern recognition, solid modeling, similarity retrieval, and VLSI design.
About the Author Hanan Samet is Professor in the Department of Computer Science at the University of Maryland, and a member of the Center for Automation Research and the Institute for Advanced Computer Studies. He is widely published in the fields of spatial databases and data structures, computer graphics, image databases and image processing, and geographic information systems (GIS), and is considered an authority on the use and design of hierarchical spatial data structures such as the quadtree and octree for geographic information systems, image processing, and computer graphics. He is the author of the two books The Design and Analysis of Spatial Data Structures and Applications of Spatial Data Structures: Computer Graphics, Image Processing and GIS. He holds a Ph.D. in computer science from Stanford University.
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