Wavelet-filter joint-transform correlation applied to the recognition of polarization-enhanced subsurface land mine patterns in highly cluttered passive imagery

Aed El-Saba; S. Alsharif; R. Stripathi

doi:10.1117/12.849546

12 May 2010 Wavelet-filter joint-transform correlation applied to the recognition of polarization-enhanced subsurface land mine patterns in highly cluttered passive imagery

Aed El-Saba, S. Alsharif, R. Stripathi

Author Affiliations +

Proceedings Volume 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI; 76961U (2010) https://doi.org/10.1117/12.849546
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

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.

Citation Download Citation

Aed El-Saba, S. Alsharif, and R. Stripathi "Wavelet-filter joint-transform correlation applied to the recognition of polarization-enhanced subsurface land mine patterns in highly cluttered passive imagery", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76961U (12 May 2010); https://doi.org/10.1117/12.849546

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