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Proceedings Paper

Multiscale shape analysis: beyond the normality and independence of noise
Author(s): Yun He; A. Hamid Krim
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Paper Abstract

In this paper, we propose a new algorithm for extracting a non smooth shape from its noisy observation. The key ideal is to project the noisy shape onto a set of orthogonal subspaces at different resolutions, and construct scale space representation gleaned from the locally smoothed shape. Using the curvature we proceed to filter the high resolution scale subspace by projecting it onto the scale which is in turn used for the reconstruction. Inspired by the conjugate mirror filter and the wavelet decomposition synergy, we propose a curvature based filter operating at different scales and with minimal knowledge about the noise statistics.

Paper Details

Date Published: 26 October 1999
PDF: 12 pages
Proc. SPIE 3813, Wavelet Applications in Signal and Image Processing VII, (26 October 1999); doi: 10.1117/12.366783
Show Author Affiliations
Yun He, North Carolina State Univ. (United States)
A. Hamid Krim, North Carolina State Univ. (United States)

Published in SPIE Proceedings Vol. 3813:
Wavelet Applications in Signal and Image Processing VII
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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