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Proceedings Paper

Smooth image segmentation via multiresolution analysis
Author(s): Jing Zhou; Xiang Fang; Bijoy K. Ghosh
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Paper Abstract

In this paper, the problem of segmentation of smooth images has been studied using multiresolution analysis. The approximated image intensity function is modeled as a quadratic polynomial with additive noise within local windows. The analysis has been carried out with the aid of a new orthonormal wavelet basis introduced in this paper. A procedure has been developed to approximate an image at a coarse resolution by dropping the components of the image in such a way that small bumps at finer resolutions are suppressed. An image segmentation scheme is proposed. It performs initial segmentation on a coarse approximation of the image, and then updates the segments of the image at a finer resolution. The proposed algorithm has been tested on a variety of real images such as human faces, natural scenes, and medical images.

Paper Details

Date Published: 11 October 1994
PDF: 11 pages
Proc. SPIE 2303, Wavelet Applications in Signal and Image Processing II, (11 October 1994); doi: 10.1117/12.188797
Show Author Affiliations
Jing Zhou, Washington Univ. (United States)
Xiang Fang, Washington Univ. (United States)
Bijoy K. Ghosh, Washington Univ. (United States)

Published in SPIE Proceedings Vol. 2303:
Wavelet Applications in Signal and Image Processing II
Andrew F. Laine; Michael A. Unser, Editor(s)

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