Identification of surface-laid mines by classification of compact airborne spectrographic imager (CASI) reflectance spectra

摘要

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. !12