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Composite training images for synthetic discriminant functions

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Abstract

The use of composite images allows more images to be included in the construction of synthetic discriminant functions without increasing the training-set cardinality. This provides lower computational overhead or allows inclusion of more training information for the same computational load. The procedure is demonstrated with the minimum-average-correlation-energy synthetic discriminant function as an example.

© 1996 Optical Society of America

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