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Proceedings Paper

Tree-structured wavelet transform for textured image segmentation
Author(s): Tianhorng Chang; C.-C. Jay Kuo
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Paper Abstract

A tree-structured wavelet transform has been developed for texture classification in our previous work. The new transform, which offers a non-redundant representation, is able to zoom into dominant frequency channels containing significant information of textures and can be interpreted as the decomposition of a 2-D function with the wavelet packet basis. In this research, we extend our work to the texture segmentation problem. A new multiscale texture segmentation algorithm based on the tree-structured wavelet transform and hierarchical fuzzy clustering technique is proposed. Numerical experiments are given to demonstrate the performance of our new algorithm.

Paper Details

Date Published: 30 November 1992
PDF: 12 pages
Proc. SPIE 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III, (30 November 1992); doi: 10.1117/12.130945
Show Author Affiliations
Tianhorng Chang, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 1770:
Advanced Signal Processing Algorithms, Architectures, and Implementations III
Franklin T. Luk, Editor(s)

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