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Hierarchical Image Analysis Using Irregular Tessellations
April 1991 (vol. 13 no. 4)
pp. 307-316

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.

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Index Terms:
hierarchical structure; picture processing; irregular tessellations; multiresolution image analysis; stochastic processes; segmentation; gray level images; picture processing; stochastic processes
Citation:
A. Montanvert, P. Meer, A. Rosenfeld, "Hierarchical Image Analysis Using Irregular Tessellations," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 4, pp. 307-316, April 1991, doi:10.1109/34.88566
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