Optimal and suboptimal detection of a target with random grey levels imbedded in non-overlapping noise

The problem of the detection of a target with random grey levels appearing on a random background is addressed. The optimal processor for any white statistics of the target's and the background's grey levels is determined. If the statistics of the grey levels are unknown, it is shown that one can approach the performance of the optimal processor by correlating the silouhette of the target with preprocessed versions of the scene and by performing the fusion of the obtained correlation planes. This result opens new perspectives for optical correlation.