Journal
PATTERN RECOGNITION LETTERS
Volume 26, Issue 10, Pages 1461-1469Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2004.11.023
Keywords
image processing; hierarchical segmentation; variational PDE; level set methods; additive operator splitting
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This paper presents an unsupervised hierarchical segmentation method for multi-phase images based on a single level set (2-phase) method and the semi-implicit additive operator splitting (AOS) scheme which is stable, fast, and easy to implement. The method successively segments image subregions found at each step of the hierarchy using a decision criterion based on the variance of intensity across the current subregion. The segmentation continues until a specified number of levels has been reached. The segmentation information for sub-images at each stage is stored in a tree data structure, and is used for reconstructing the segmented images. The method avoids the complicated governing equations of the multi-phase segmentation approach, and appears to converge in fewer iterations. The method can easily be parallelized because the AOS scheme decomposes the equations into a sequence of one dimensional systems. (c) 2004 Elsevier B.V. All rights reserved.
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