A three-dimensional (3-D) spatiotemporal prediction-error filter (PEF) is used to enhance foreground/background contrast in (real and simulated) sensor image sequences. Relative velocity is utilized to extract point targets that would otherwise be indistinguishable with spatial frequency alone. An optical-flow field is generated using local estimates of the 3-D autocorrelation function via the application of the fast Fourier transform (FFT) and inverse FFT. Velocity estimates are then used to tune in a background-whitening PEF that is matched to the motion and texture of the local background. Finite impulse response (FIR) filters are designed and implemented in the frequency domain. An analytical expression for the frequency response of velocity-tuned FIR filters, of odd or even dimension with an arbitrary delay in each dimension, is derived.
Hugh L. Kennedy,
"Multidimensional digital filters for point-target detection in cluttered infrared scenes," Journal of Electronic Imaging 23(6), 063019 (17 December 2014). https://doi.org/10.1117/1.JEI.23.6.063019