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2 August 1999 Detection of surface-laid mine fields in VNIR hyperspectral high-spatial-resolution data
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Abstract
The feasibility of detecting surface-laid and, in some circumstances, buried mines by analysis of visible to near- IR (VNIR) hyperspectral imagery has been demonstrated by the authors in previous studies. An important factor in the practical success of such technology is being able to achieve the necessary spatial and spectral resolution to allow discrimination of mines from background. With some restrictions, both can be improved by increasing the instrument data output rate or decreasing the platform speed and both can be traded off against one another. The optimum trade-off must be determined for a given problem, including the choice of algorithm. Airborne VNIR hyperspectral data were collected over several controlled surface-laid mine fields using a casi hyperspectral imager and a helicopter. The combination of the imager's high speed data recording coupled with the low airspeed of the helicopter enabled the collection of hyperspectral data ranging from four 136 nm wide spectral bands at 10 cm resolution to nine 60 nm wide spectral bands at 20 cm resolution. Each mine field contained a variety of mines ranging form small anti- personnel mines to large anti-vehicle mines. An assessment of the feasibility and practicality of using airborne hyperspectral data to detect various surface-laid mines and mine fields was conducted. In addition, the trade-offs between spectral and spatial resolution for the detectability of surface-laid miens and mine fields are discussed.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen Binal Achal, Clifford D. Anger, John E. McFee, and Robert W. Herring "Detection of surface-laid mine fields in VNIR hyperspectral high-spatial-resolution data", Proc. SPIE 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, (2 August 1999); https://doi.org/10.1117/12.357103
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