Abstract: A process for reducing background clutter of a scene, and isolating an object of interest. The process includes calculating a minimum output from a plurality of appropriately configured anti-median filters representing a minimum difference processor (MDP) filter. In a first embodiment, the MDP filter includes a (5.times.5) matrix of elements wherein each element has an intensity value representation of the scene. A first anti-median filter array is configured as a horizontal array of 5 pixel elements in which the center element of the matrix is the center element of the horizontal array. A median value of the 5 elements of the horizontal array is determined, and is subtracted from the value of the center element to determine an anti-median value of the horizontal array. The same process is performed for a vertical 5 element anti-median array, and two diagonal 5 element anti-median arrays, all including the center element of the matrix as the center common element of the arrays.

Abstract: A hierarchical object recognition method for aggregation, interpretation and classification of information from multiple sensor sources on the detection feature attribute level. The system extracts information derived from each sensor source to obtain detections and their feature attributes. At least two processing streams, one for each sensor source, are provided for converting the detections and their feature attributes into hypotheses on identity and class of detected objects. The detections are shared and combined between the two processing streams using hierarchical information fusion algorithms to determine which ones of the hypotheses on identity and class of detected objects have sufficient probabilities for classifying the information.

Abstract: Moving objects (36) are detected by processing images through a spatial filter (42) and positional shifter (46), which shifts the image by an amount reflecting a line of sight velocity hypothesis of the objects. The images are stacked together by a stacker 48, causing the intensity of an object moving at the line of sight velocity hypothesis to increase, and other objects to be blurred. The stacked image is spatially filtered (50) to remove the blurred objects and linear artifacts, and the moving objects (36) of interest are selected according to their increased intensities. In a practical system, the images are processed with a range of velocity hypotheses to identify both the object and the true line of sight velocity.