Share Email Print

Proceedings Paper

Clutter reduction and target detection enhancement using wavelet transform techniques
Author(s): Xiangyang Yang; Don A. Gregory; Peter S. Erbach
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In this paper, a multichannel optical wavelet processor and a matching pursuit processor capable of enhancing the detection of cluttered targets are presented. Wavelet functions have zero-mean and are virtually band-pass filters. In many cases, targets and clutter are separable in the spatial spectral domain. Therefore, by selecting wavelet functions that represent features of targets but are insensitive to that of clutter, targets can be extracted from the input scene while clutter is suppressed. Due to dyadic sampling, a multichannel optical wavelet processor with a limited number of channels can detect regions of interest for different targets. With matching pursuit decomposition, features of targets are extracted and represented in a few wavelets known as coherent structure; whereas clutter and noise are diluted across the dictionary. Clutter and noise can then be effectively removed from the signal by a simple thresholding operation. A time-frequency energy distribution can be derived from matching pursuit decomposition, which contains no interference terms and thus clearly characterized the input signal in the time-frequency plane. Optical architectures of these processors are described. Simulated and experimental results are provided.

Paper Details

Date Published: 28 March 1995
PDF: 15 pages
Proc. SPIE 2490, Optical Pattern Recognition VI, (28 March 1995); doi: 10.1117/12.205767
Show Author Affiliations
Xiangyang Yang, Univ. of New Orleans (United States)
Don A. Gregory, Univ. of Alabama in Huntsville (United States)
Peter S. Erbach, Univ. of Alabama in Huntsville (United States)

Published in SPIE Proceedings Vol. 2490:
Optical Pattern Recognition VI
David P. Casasent; Tien-Hsin Chao, Editor(s)

© SPIE. Terms of Use
Back to Top