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Proceedings Paper

Identification of surface-laid mines by classification of compact airborne spectrographic imager (CASI) reflectance spectra
Author(s): Stephen Binal Achal; John E. McFee; Clifford D. Anger
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Paper Abstract

A visible wavelength imaging method of identifying surface-laid mines from an airborne platform is described. A Compact Airborne Spectrographic Imager (CASI) collects multispectral radiometric images of mines and backgrounds which are converted to reflectance images using an incident light sensor. Mines are identified by classifying reflectance spectra in two ways. The first classifies individual pixels using the linear correlation coefficient as a measure of spectral similarity while the second classifies spectra using a variant of linear spectral unmixing in which the majority spectral members within an image are treated as background. In scanning manlift imagery of replica mines, targets were discriminated from a variety of background types, even when partially obscured by vegetation, for widely varying illuminations caused by diurnal and seasonal variations, sky conditions, and sun angles. In preliminary practical tests, the CASI was flown over various agricultural fields in which subpixel-size mine-like targets were laid. Visually undetectable targets were detected with good results. Comparison of classifiers revealed that the correlation method is better for high spatial resolution data. When the targets were subpixel in size, the end member analysis had a higher probability of detection than the correlation method, but had more false alarms.

Paper Details

Date Published: 20 June 1995
PDF: 12 pages
Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); doi: 10.1117/12.211328
Show Author Affiliations
Stephen Binal Achal, Itres Research Ltd. (Canada)
John E. McFee, Defence Research Establishment Suffield (Canada)
Clifford D. Anger, Itres Research Ltd. (Canada)

Published in SPIE Proceedings Vol. 2496:
Detection Technologies for Mines and Minelike Targets
Abinash C. Dubey; Ivan Cindrich; James M. Ralston; Kelly A. Rigano, Editor(s)

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