We present a new approach aimed at fast multiframe registration of airborne video collected by moving platforms such as unmanned aerial vehicles. Registration is used to enable separating the moving objects from the stationary background, which is similar to estimating the egomotion of the sensor. The proposed registration algorithm is used to match the moving background and remap video frames into a common co-ordinate system in order to stabilize that segment of video. The major modules include dense feature detection, sparse prominent edge and corner-based feature block identification, feature block region matching to extract control points, confidence weighted robust projective transformation estimation and image warping to register a segment of frames within a given temporal window. The proposed method is shown to produce good results with small image registration error.