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Synthetic Discriminant Functions For Target Correlation

Synthetic discriminant functions (SDFs) are used to construct digital filters for identifying and registering tank targets on 8-bit digitized forward, looking infrared (FLIR) imagery through correlation. The synthesis and testing of SDFs which control the shape of the correlation surface about the peak are discussed. This is effected by shifting the reference images in the + x and ± y directions and encoding these shifted images onto the filter. The advantages of shifting the reference images include sharper target correlation peaks, suppression of sidelobes on the correlation surface, correlation peaks that occur closer to the registration point of the target, and better overall target discrimination. The reference and test imagery consist of aspect-varying tank images, with a high degree of clutter resident on the test set imagery. Successive filter reference images are chosen on the basis of being quantitatively most dissimilar, in a correlation sense, than other images already resident on the filter. Filter construction techniques are discussed, and train and test set classification results are presented.