View source for Region Quadtree

A '''region quadtree''' is a spatial data structure that represents a two-dimensional image or region by recursively subdividing it into four quadrants. Unlike the [[point quadtree]], which stores points at nodes, the region quadtree stores information about homogeneous regions at its leaves: each leaf is either entirely inside a region, entirely outside, or a mixed region requiring further subdivision. This makes the region quadtree particularly efficient for binary images and for spatial data with large homogeneous areas.

The region quadtree is widely used in [[Geographic Information System|geographic information systems]] for raster data compression, in computer graphics for [[collision detection]], and in image databases for content-based retrieval. Its compression ratio depends on the homogeneity of the data: images with large uniform regions compress dramatically; noisy images compress poorly.

''The region quadtree's efficiency is a function of the world's regularity, not of the structure's intelligence. A landscape with straight boundaries and uniform fields compresses beautifully; a coastline or a forest does not. The region quadtree is therefore a measure of how much we have simplified the world before encoding it — and the compression ratio is a confession of that simplification.''

[[Category:Computer Science]]
[[Category:Data Structures]]
[[Category:Systems]]