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Simulation of infrared backgrounds using two-dimensional models

Analysis and simulation of smart munitions requires imagery for the munition's sensor to view. The imagery is usually infrared and depicts a target embedded in a background. Mathematical models of such imagery are useful to munitions researchers. A mathematical model can synthesize a test scenario at a cost much less than that of actual data acquisition. To date, most research has focused on the modeling targets. It is essential, however, to test a munition's target acquisition algorithms on images containing targets superimposed on a wide variety of backgrounds. Consequently, there is a need for accurate models of infrared backgrounds. Useful models are difficult to create because of the complexity and diversity of imagery viewed by smart munition sensors. A model of IR backgrounds is presented that will, given a textured image, generate another image. The synthetic image, although distinctly different from the original, has the general visual characteristics and the first and second-order statistics of the original image. In effect, the synthetic image looks like a continuation of the original scene, as if another picture of the scene were taken adjacent to the original. The model is an FIR kernel convolved with an excitation function, noise added to the result, and followed by histogram modification. The paper describes a procedure for deriving the correct FIR kernel using a signal enhancement algorithm, and reports a demonstration of the model in which it is used to mimic several diverse textured images.