Reduction of surface clutter in infrared images with visual-wavelength measurements

This paper addresses the problem of using visual-wavelength images to reduce surface clutter when detecting buried land mines using infrared imaging. The visual wavelength images capture the uneven sunlight absorption of the surface causing clutter in the infrared image. By considering the clutter in the infrared image to be a linear filtered version of the visual wavelength image, the clutter is reduced by first estimating the filter using an adaptive least-squares algorithm and then subtracting the estimated clutter from the original infrared image. Experiments on real data shows that the method performs well when detecting buried objects in sand with surface structure. Hence, by using additional measurements taken in the the visual wavelengths, it is possible to remove the influence of the surface structure, that otherwise causes severe clutter, resulting is falsely detected targets