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Proceedings Paper

Wavelet approach to detect discontinuities of intensity functions for minefield classification
Author(s): Robert R. Muise; Charles K. Chui
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Paper Abstract

An inhomogeneous point process is assumed to govern the observation of a minefield embedded in background clutter. Basic assumptions are that the clutter process is distributed as an inhomogeneous Poisson process with a smooth intensity function and that the minefield process is spatially bounded. This leads to a scheme involving estimation of the underlying intensity of the observed process and detection of intensity discontinuities to locate minefield boundaries. A tensor product cubic spline with small bandwidth is used for original intensity estimation. Subsequently, an oversampled spline-wavelet decomposition is applied to the estimated intensity and the maximum modulus of the wavelet transform is used to detect 'discontinuities' in the minefield boundaries when the original smoothness assumptions about the clutter process are valid. Some simulated results are presented for several background clutter processes at different modulus of continuity.

Paper Details

Date Published: 20 June 1995
PDF: 12 pages
Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); doi: 10.1117/12.211349
Show Author Affiliations
Robert R. Muise, Naval Surface Warfare Ctr. (United States)
Charles K. Chui, Texas A&M Univ. (United States)

Published in SPIE Proceedings Vol. 2496:
Detection Technologies for Mines and Minelike Targets
Abinash C. Dubey; Ivan Cindrich; James M. Ralston; Kelly A. Rigano, Editor(s)

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