29 October 1997 Detection of moving targets in time-sequenced imagery using statistical background rejection
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Abstract
A method of detecting dim moving targets in highly cluttered time- varying image sequences is presented. These targets are sufficiently faint that they cannot be detected in individual image frames, so a track-before-detect method is required. This method is based on the analysis of a single 2-D composite image in which movement shows up as bright swaths. The composite image is constructed by computing the absolute values of the differences between neighboring image frames and then, for each pixel, taking the maximum value of these differences over time. Image registration is employed where required. Moving targets are detected using a wavelet-based feature extraction algorithm, in which the bright regions in the composite image are decomposed into bar features. Background rejection is employed to remove sensor noise and other changes in brightness not associated with movement, for example changes in illumination. Initial clutter rejection is based on a given threshold exceedence rate estimated from the multiresolution background statistics of feature intensity. Further false track rejection involves a space-time analysis of image frame differences in the neighborhood of each bright region, where genuine movement appears as connected diagonal swaths. Results so far indicate that this approach to moving target detection is highly effective when backgrounds are highly correlated in time. No assumptions about the behavior of the target motion are required, the only limitation being that the targets are moving sufficiently quickly to traverse several pixels during the total time interval under analysis.
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Graham H. Watson, Graham H. Watson, Sharon K. Watson, Sharon K. Watson, "Detection of moving targets in time-sequenced imagery using statistical background rejection", Proc. SPIE 3163, Signal and Data Processing of Small Targets 1997, (29 October 1997); doi: 10.1117/12.279539; https://doi.org/10.1117/12.279539
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