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Missile warning receivers are electronic support systems which are widely used for the protection of fixed and rotary wing aircraft against infrared guided missiles. Proposed methodology for the detection of missile threats in missile warning receivers depends upon the estimation of background from consecutive image frames. By removing the estimated background from the images, foreground objects (missile plume images) are detected. In this study, “Speeded-Up Robust Features (SURF)” methodology based on feature correspondence is used for the estimation of background motion.