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Image coding by adaptive tree-structured segmentation

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1 Author(s)
Xiaolin Wu ; Dept. of Comput. Sci., Univ. of Western Ontario, London, Ont., Canada

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

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Information Theory, IEEE Transactions on  (Volume:38 ,  Issue: 6 )