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Anisotropic diffusion pyramids for image segmentation

Scott T. Acton(1), Allen C. Bovik(2), and Melba M. Crawford (3)

(1): School of Electrical and Computer Engineering, Oklahoma State University
(2): Electrical Engineering, University of Texas at Austin
(3): Center for Space Research, University of Texas at Austin

E-mail: crawford@csr.utexas.edu

ABSTRACT

We introduce the Anisotropic Diffusion Pyramid (ADP), a structure for multiresolution image processing. We also develop the ADP for use in region-based segmentation. The pyramid is constructed using the anisotropic diffusion equations, creating an efficient scale-space representation. Segmentation is accomplished using pyramid node linking. Since anisotropic diffusion preserves edge localization as the scale is increased, the region boundaries in the coarse-to-fine ADP segmentation are accurately delineated. An application to segmentation of remotely sensed data is provided. The results of ADP segmentation are compared to Gaussian-based pyramidal segmentation. The examples show that the ADP has a superior ability to subdivide the image into integral groupings, minimizing the error in boundary localization and in pixel intensity.

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Last Modified: Tue July 13, 1999
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