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Proceedings Paper

Wavelet-filter joint-transform correlation applied to the recognition of polarization-enhanced subsurface land mine patterns in highly cluttered passive imagery
Author(s): Aed El-Saba; S. Alsharif; R. Stripathi
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Paper Abstract

Efficient recognition and clearance of subsurface land mine patterns has been one of the challenging humanitarian and military tasks. Among the several subsurface land mine patterns recognition techniques available, passive imaging techniques are more convenient, safer with good probability of recognition. There exist extensive applications where the joint-transform correlation algorithms have been used for efficient pattern recognition. However, among the several pattern recognition algorithms exist for subsurface land mines, the joint-transform correlation ones has been underrepresented. This paper presents the application of an efficient wavelet-filter joint transform correlation (WFJTC) algorithm for the recognition of passive imagery of subsurface land mines in highly cluttered scenarios, using intensity and polarization-based imagery. We further improve the recognition efficiency of the WFJTC proposing a combined optical-digital enhancement approach. Improvements will be justified using correlation performance metrics.

Paper Details

Date Published: 12 May 2010
PDF: 9 pages
Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76961U (12 May 2010); doi: 10.1117/12.849546
Show Author Affiliations
Aed El-Saba, Univ. of South Alabama (United States)
S. Alsharif, Univ. of South Alabama (United States)
R. Stripathi, Univ. of South Alabama (United States)


Published in SPIE Proceedings Vol. 7696:
Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI
Firooz A. Sadjadi; David P. Casasent; Steven L. Chodos; Abhijit Mahalanobis; William E. Thompson; Tien-Hsin Chao, Editor(s)

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