Parallel processing of regions represented by linear quadtrees
Computer Vision, Graphics, and Image Processing
Parallel processing of linear quadtrees on a mesh-connected computer
Journal of Parallel and Distributed Computing
The design and analysis of spatial data structures
The design and analysis of spatial data structures
Vectorization of tree traversals
Journal of Computational Physics
A parallel hashed Oct-Tree N-body algorithm
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
Multidimensional access methods
ACM Computing Surveys (CSUR)
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
An effective way to represent quadtrees
Communications of the ACM
Image compression for fast wavelet-based subregion retrieval
Theoretical Computer Science - computing and combinatorics
Memory-efficient A* heuristics for multiple sequence alignment
Eighteenth national conference on Artificial intelligence
Optimal parallel all-nearest-neighbors using the well-separated pair decomposition
SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science
IEEE Transactions on Image Processing
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This paper presents vectorized methods of construction and descent of quadtrees that can be easily adapted to message passing parallel computing. A time complexity analysis for the present approach is also discussed. The proposed method of tree construction requires a hash table to index nodes of a linear quadtree in the breadth-first order. The hash is performed in two steps: an internal hash to index child nodes and an external hash to index nodes in the same level (depth). The quadtree descent is performed by considering each level as a vector segment of a linear quadtree, so that nodes of the same level can be processed concurrently.