Efficient CFAR detection of line segments in a 2-D image

A computationally efficient algorithm is proposed for detecting line segments in an image of additive, i.i.d. (independent, identically distributed) Gaussian noise. Meteors, satellites, or other moving objects may be optically detected using the algorithm. A CFAR (Constant False Alarm Rate) characteristic is designed into the algorithm to give equal probabilities of false alarm for all streak lengths. Compared to the 2-D optimum matched filter approach, the algorithm loses 2 dB in signal-to-noise ratio, but requires hundreds of times less computation.