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: 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.

Abstract: A method and apparatus for detecting an object of interest against a cluttered background scene. In a first preferred embodiment the sensor tracking the scene is movable on a platform such that each frame of the video representation of the scene is aligned, i.e., appears at the same place in sensor coordinates. A current video frame of the scene is stored in a first frame storage device (14) and a previous video frame of the scene is stored in a second frame storage device (20). The frames are then subtracted by means of an invertor (24)and a frame adder (28) to remove most of the background clutter. The subtracted image is put through a first leakage reducing filter, preferably a minimum difference processor filter (32). The current video frame in the first frame storage device (14) is put through a second leakage-reducing filter, preferably minimum difference processor filter (36).

Abstract: Three image frames containing an object of interest and background clutter are taken at successive time intervals and stored in memory. The background of images A, B and C are registered preferably using an area correlator 12. A median filter 16 is used to select a median value from the registered image frames. Then, subtractor 18 serves to subtract the median pixel values from one of the image frames. This difference output is then thresholded to provide a binary signal whose pixel values exceeding the threshold levels are generally associated with the position of the moving object.

Abstract: Target tracking capability is provided by a synergistic tracker system (5) which includes both a correlation tracker (30) and an object tracker (40) for processing sensor data input (10) and for generating tracking error signals (80). The operation of the synergistic tracker system is controlled by a central processing unit (70). The system operates by first correlating a reference region image with a portion of a current digitized image provided by an analog to digital converter (20). Secondly, the object tracker provides a precisely defined trackpoint for an object within the current image. The correlation tracker stabilizes and limits the portion of the digitized image that the object tracker must operate upon. Stabilizing and limiting this portion of the digitized image reduces the object tracker's sensitivity to background clutter and sensitivity to a loss of lock induced by sensor motion. The object tracker provides a non-recursive update for the correlation's reference region image.

Abstract: A method and apparatus for correlating two signals representing a live image and a reference image are disclosed. The reference signal is processed to provide a polarity bit and mask bit for each pixel position in the reference image. The processed video signal is stored in a memory 20 and used in a convolver and summer section 18 in which the polarity bits between the reference and live images are gated by gate 17 and are used in generating a correlation output from summer 23. However, the polarity bits do not affect the correlation output if the logical output from gate 19 is of a given state which occurs if the associated mask bits indicate that the gradient value at the particular pixel position does not exceed certain minimum threshold values.

Abstract: A conventional tracker 14 is used to continually aim a sensor 12 at a flying object so that it is located in substantially the same spatial location in a plurality of image frames taken at different times. Thus, the object remains in about the same spatial position in each image frame while the background clutter generally changes. By processing two or more of the image frames it is possible to calculate a more precise aimpoint for the object than is generally provided by the track point.

Abstract: A system (20) for identifying and tracking targets in an image scene having a highly cluttered background. An imaging sensor and processing subsystem (21) provides a video image of the image scene. A size identification subsystem (23) removes background clutter from the image by filtering the image to pass objects whose sizes are within a predetermined size range. A feature analysis subsystem (24) analyzes the features of those objects which pass through the size identification subsystem and determines if a target is present in the image scene. A gated tracking subsystem (25) and scene correlation and tracking subsystem (26) track the target objects and image scene, respectively, until a target is identified. Thereafter, the tracking subsystems lock onto the target identified by the system (20). Several methods relating to target acquisition are also disclosed.

Abstract: Apparatus for processing applied signals indicative of an image scene in order to provide output signals representative of objects in the scene whose sizes are within a predetermined size range. Combinations of median and anti-median filters are employed in serial and parallel configurations to produce the desired size filtering. The basic system comprises first filter means for providing first output signals indicative of objects whose sizes are within a first preselected size range. Second filter means are employed which provide second output signals indicative of objects whose sizes are within a second preselected size range. At least one of the two preselected size ranges contain object sizes within the predetermined size range. Circuit means are provided for coupling the output signals from the two filters in a manner which generates output signals indicative of objects whose sizes are within the predetermined range.