Toward a unifying optimal approach to mine detection problems

Automatic mine detection has recently become a subject of great importance to U.S. Navy. A number of approaches to this problem have been suggested so far. Current algorithms however do not provide sufficiently high performance results, especially in cases where mines are embedded in clutter. A thorough and fundamental understanding of target detection and recognition techniques is needed in order to significantly enhance the capabilities of automatic detection systems. We discuss here a possible approach to this problem, based on a theoretical model for image acquisition, that allows mine detection to be formulated as an inverse problem. New and near optimal algorithms may be developed as attempts to solving this problem.

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