Paper
26 April 2010 Improved subsurface land mine recognition using high-boost fusion between passive Stokes vector imagery
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Abstract
Detection and clearance of subsurface land mines has been one of the challenging humanitarian and military tasks. Passive polarization-based imagery has played important role achieving this task. This paper presents new fusion technique where polarization-based imagery is fused with traditional intensity imagery using high-boost approach. The main idea of the high-boost approach used in this paper is to give the polarization imagery obtained from the Stokes vector imagery more weight in forming the final fused image. It is shown that the proposed technique improves the recognition of surface land mines. This improvement is shown using correlation performance metrics derived from wavelet-filter joint-transform correlation algorithm used for pattern recognition.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aed El-Saba "Improved subsurface land mine recognition using high-boost fusion between passive Stokes vector imagery", Proc. SPIE 7672, Polarization: Measurement, Analysis, and Remote Sensing IX, 76720S (26 April 2010); https://doi.org/10.1117/12.850536
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image fusion

Land mines

Polarization

Wavelets

Fourier transforms

Polarimetry

Detection and tracking algorithms

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