Abstract

Algorithms have been developed for discriminating image signals on a background of bimodal Gaussoid pulse noise under conditions of complete a priori indeterminacy concerning the image-signal distribution. The algorithms are based on a new optimality criterion that combines the minimum of the unconditional skip probability with the maximum correct-detection probability at limited levels of unconditional false-alarm and correct-nondetection probabilities. The results of numerical studies of algorithms are presented that show that they are of higher quality than known nonoptimal procedures, as well as than the optimal algorithm under the condition of complete a priori signal indeterminacy.

© 2010 Optical Society of America

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