Image coding by adaptive tree-structured segmentation

  • Authors:
  • X. Wu

  • Affiliations:
  • Dept. of Comput. Sci., Univ. of Western Ontario, London, Ont.

  • Venue:
  • IEEE Transactions on Information Theory
  • Year:
  • 2006

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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