Image Data Structures and Converting Algorithms

Researches on data structures are always combined with algorithms. The format of data determines the ways of obtaining and processing the data. In image processing area, there are three image data structures, raster, vector, and quadtree. Each has their own advantages and disadvantages, and is suitable for different requirements of operations and processes. A sophisticated image processing system or geographic information system should meet different needs by using different features of different structures so that the system can improve the efficiency of time and space when storing, processing, retrieving, and outputting image data. This needs converting algorithms between the data structures. Previous researches have been narrowed in theories of traditional data structures or algorithms. The research involved in this book covers the most commonly used image data structures, especially the 2-Dimensional Run Encoding Quadtrees which are the latest development of quadtree structure, and converting algorithms between the 2DRE quadtrees and other structures and describes the applications of the structures and algorithms in GIS.

Dr. Ke Xiao is from China. He was self-taught for middle and high school. He got B.E. in Computer Science at University of Science and Technology, Harbin; M.Sc in Mapping and Remote Sensing at Chinese Academy of Sciences; and PhD in Remote Sensing and GIS in 2003 at Louisiana State University. Now he is faculty in LSU Health Sciences Center, USA.