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A region quadtree may also be used as a variable resolution representation of a data field.
Each such interval corresponds to a square in the quadtree.
A quadtree is a tree data structure in which each internal node has exactly four children.
A quadtree coding structure will be used with the superblocks.
The data itself is saved in a Quadtree.
A quadtree is used to represent the field.
As mentioned, the Z-ordering can be used to efficiently build a quadtree for a set of points.
The following pseudo code shows one means of implementing a quadtree which handles only points.
Split-and-merge segmentation is based on a quadtree partition of an image.
As the name suggests, it uses hash tables to store the nodes of the quadtree.
The region quadtree is a type of trie.
A non-compressed quadtree can be built by restoring the missing nodes, if desired.
The following method inserts a point into the appropriate quad of a quadtree, splitting if necessary.
A quadtree is simply a 2D octree.
The point quadtree is an adaptation of a binary tree used to represent two dimensional point data.
The result of this is a compressed quadtree, where only nodes containing input points or two or more children are present.
Rather than building a pointer based quadtree, the points can be maintained in sorted order in a data structure such as a binary search tree.
Finkel and J.L. Bentley created the data structure called the quadtree.
While a quadtree trivially has far more overhead than other simpler representations (such as using a matrix of bits), it allows for various optimizations.
If the quadtree is compressed, the predecessor node found may be an arbitrary leaf inside the compressed node of interest.
For example, the temperatures in an area may be stored as a quadtree, with each leaf node storing the average temperature over the subregion it represents.
Prior to geomipmapping, techniques such as quadtree rendering were used to divide the terrain into square tiles created by binary division with quadratically diminishing size.
Each square in the quadtree has a side length which is a power of two, and corner coordinates which are multiples of the side length.
The arrangement of CUs within a CTB is known as a quadtree since a subdivision results in four smaller regions.
These algorithms arrange all particles in a tree, a quadtree in the two-dimensional case and an octree in the three-dimensional case.