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Contrasted statistical processing algorithm for obtaining improved target detection performances in an IR cluttered environment

This paper presents a contrasted statistical processing approach to obtain improved probabilities of false alarm when performing automatic target detection. The technique is based upon analyzing each sector of the image and comparing it with surrounding windows in which the desired statistical property is calculated. The contrast of the statistical property is extracted using the prediction or the prediction-correction equations. The contrast of the statistical property is shown to be a good discriminator of the target from its background allowing the reduction of the detection threshold applied over the stationary region while maintaining a constant false alarm probability.