We present a study of a family of maximum average correlation height (MACH) filters. MACH filters were introduced by Mahalanobis et al., and several modifications such as the extended MACH (EMACH) and generalized MACH (GMACH) have been introduced to enhance the utility of the MACH filter approach. A comparison between the different filtering approaches and processing techniques is presented for the specific case of laser radar (ladar) imagery. The comparison utilizes both synthetic data for training and testing in one case, and synthetic training data and collected ladar imagery for testing in the second case. The results indicate that the GMACH variant of MACH filters is superior to both MACH and EMACH filters for the case of laser radar.