Given multiple images of the earth's surface f r o m dual-band infrared sensors, our system fuses information from the sensors t o reduce the eflects of clutter and improve the ability to detect buried or surface target sites. Supervised learning pattern classifiers (including neural networks) are used. W e present resuNs of ezpen'ments t o detect buried land mines from real data, and evaluate the usefulness of fusing information from multiple sensor types. The novelty of the work lies mostly i n the combination of the algorithms and their application t o the very important and currently unsolved problem of detecting buried land mines from an airborne standoff platform.
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