Abstract
A novel target detection technique is developed in this paper for hyperspectral imagery. The proposed technique involves a Gaussian filter to process the reference target signature as well as the unknown pixel signature from the given input scene. After performing correlation operation between the signatures, a post-processing scheme is employed to decide whether the specific pixel contains the target material. Theoretical analyses and computer simulation results presented in this paper show that the technique can successfully overcome the problem of variations in the target signature due to changes in the environment and addition of noise to the input scene. Investigation on real-life hyperspectral imagery proves that the proposed technique can successfully detect the potential targets present in the input scene without generating any significant amount of false alarm.
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