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13 August 1993 Background and target randomization and root mean square (RMS) background matching using a new deltaT metric definition
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Abstract
EO/IR/Laser detection of a target amidst clutter/background is a difficult problem often treated with simplistic models. Unlike noise, clutter is more complex, neither spectrally white nor statistically Gaussian. Therefore, it is insufficient to lump clutter with noise and use standard detection curves. Battelle has produced image randomization software called BATRAN (Background and Target Randomization) which computes various types of statistical distributions to randomize background and target pixels separately. The types of statistics implemented include exponential, Gaussian, log-normal, and Rice distributions for both the background and target. In an effort to identify a more robust and accurate (Delta) T metric definition for background and target matching, Battelle also developed a new (Delta) T metric definition and its equation using RMS pixel-based higher order statistics for the background and target signature pixel data in a scene image. This new (Delta) T metric provides a better estimate of true signature difference between the background/clutter and target, enabling more accurate matching of the background/clutter and target for use in sensor detection performance assessment.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Howard C. Choe, Thomas J. Meitzler, and Grant R. Gerhart "Background and target randomization and root mean square (RMS) background matching using a new deltaT metric definition", Proc. SPIE 1967, Characterization, Propagation, and Simulation of Sources and Backgrounds III, (13 August 1993); https://doi.org/10.1117/12.151080
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