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<p>A novel multiresolution image analysis technique based on hierarchies of irregular tessellations generated in parallel by independent stochastic processes is presented. Like traditional image pyramids these hierarchies are constructed in a number of steps on the order of log(image-size) steps. However, the structure of a hierarchy is adapted to the image content and artifacts of rigid resolution reduction are avoided. Two applications of these techniques are presented: connected component analysis of labeled images and segmentation of gray level images. In labeled images, every connected component is reduced to a separate root, with the adjacency relations among the components also extracted. In gray level images the output is a segmentation of the image into a small number of classes as well as the adjacency graph of the classes.</p>
hierarchical structure; picture processing; irregular tessellations; multiresolution image analysis; stochastic processes; segmentation; gray level images; picture processing; stochastic processes

A. Rosenfeld, A. Montanvert and P. Meer, "Hierarchical Image Analysis Using Irregular Tessellations," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 13, no. , pp. 307-316, 1991.
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