The use of GTFR with cone shaped kernel for motion estimation

A method for estimating 2D image sequences using the generalized time-frequency representation (GTFR) is presented. The performance characterization is based on 20000 simulated noisy images. The results show that even with a signal to noise ratio (SNR) of 5 db, rectangular objects of at least 4 pixels in length and width can be detected, to within 2.5 pixel location accuracy. The misdetection rate is near zero, and the average false detection rate is 0.06 false objects per frame of 64×64 size in a 5 db SNR environment. With -1 db SNR, objects can be detected within 5 pixel accuracy. The misdetection rate for this case is near zero and the average false detection rate is 1.6 false objects per frame of 64×64 size. The method is also applied to an image sequence obtained from a 747 takeoff scene. The 747 takeoff speed was predicted to be 142 kts, which is well within the typical range of 140 to 150 kts