Abstract
Window operations serve as the basis of a number of queries that can be posed in a spatial database. Examples of window-based queries include the exist query (i.e., determining whether or not a spatial feature exists inside a window), the report query (i.e., report the identity of all the features that exist inside a window), and the select query (i.e., determine the locations covered by a given feature inside a window). Often spatial databases make use of a quadtree decomposition, which yields a set of maximal blocks, to enable the features to be accessed quickly without having to search the entire database. One way to perform a window query is to decompose the window into its maximal quadtree blocks. An algorithm is described for decomposing a two-dimensional window into its maximal quadtree blocks inO(nlog logT) time for a window of sizen×n in a feature space (e.g., an image) of sizeT×T (e.g., pixel elements).
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The support of the National Science Foundation under Grant IRI-9017393 is gratefully acknowledged.
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Aref, W.G., Samet, H. Decomposing a window into maximal quadtree blocks. Acta Informatica 30, 425–439 (1993). https://doi.org/10.1007/BF01210594
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DOI: https://doi.org/10.1007/BF01210594