Title :
Image coding by adaptive tree-structured segmentation
Author_Institution :
Dept. of Comput. Sci., Univ. of Western Ontario, London, Ont., Canada
fDate :
11/1/1992 12:00:00 AM
Abstract :
A new algorithmic approach to segmentation-based image coding is proposed. A good compromise is achieved between segmentation by quadtree-based decomposition and by free region-growing in terms of time complexity and scene adaptability. Encoding is to recursively partition an image into convex n-gons, 3⩽n⩽8, until the pixels in the current n-gon satisfy a uniformity criterion. The recursive partition generates a valid segmentation by aligning the polygon boundaries with image edges. This segmentation is embedded into a binary tree for compact encoding of its geometry. The compressed image is sent as a labeled pointerless binary tree, and decoding is simply polygon filling. High compression ratios are obtained by balancing the accuracy and geometric complexity of the image segmentation, a key issue for segmentation-driven image coding that was not addressed before. Due to its tree structure, the method is also suitable for progressive image coding
Keywords :
computational complexity; computational geometry; data compression; image coding; image segmentation; trees (mathematics); adaptive tree-structured segmentation; binary tree; compact encoding; convex n-gons; decoding; free region-growing; geometric complexity; high compression ratio; image coding; image edges; labeled pointerless binary tree; polygon boundaries; polygon filling; progressive image coding; quadtree-based decomposition; recursive partition; scene adaptability; time complexity; Binary trees; Decoding; Encoding; Filling; Geometry; Image coding; Image segmentation; Layout; Partitioning algorithms; Pixel;
Journal_Title :
Information Theory, IEEE Transactions on