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dc.contributor.authorYin, Xiangen_US
dc.date.accessioned2010-03-09T20:23:04Z
dc.date.available2010-03-09T20:23:04Z
dc.date.issued2010-03-09T20:23:04Z
dc.identifier.urihttp://hdl.handle.net/10464/2952
dc.description.abstractSpatial data representation and compression has become a focus issue in computer graphics and image processing applications. Quadtrees, as one of hierarchical data structures, basing on the principle of recursive decomposition of space, always offer a compact and efficient representation of an image. For a given image, the choice of quadtree root node plays an important role in its quadtree representation and final data compression. The goal of this thesis is to present a heuristic algorithm for finding a root node of a region quadtree, which is able to reduce the number of leaf nodes when compared with the standard quadtree decomposition. The empirical results indicate that, this proposed algorithm has quadtree representation and data compression improvement when in comparison with the traditional method.en_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectSpatial data infrastructuresen_US
dc.subjectComputer algorithmsen_US
dc.titleQuadtree representation and compression of spatial dataen_US
dc.typeElectronic Thesis or Dissertationen_US
dc.degree.nameM.Sc. Computer Scienceen_US
dc.degree.levelMastersen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.degree.disciplineFaculty of Mathematics and Scienceen_US


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