Abstract:
Spatial 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.
