The regularization operator (A) should be designed based on the expected model covariance Tarantola (1986). Since we are particularly concerned with the effects of poor illumination, we need to design A to compensate for these effects. In this case, since our downward continuation operator or CAM operator will create a model that is a cube of depth, CRPX, CRPY (for the CAM operator), and phx, we can expect illumination problems to appear as gaps in events in the CRP plane(s) and along the phx axis. Prucha et al. (2001) demonstrated the use of steering filters Clapp et al. (1997) as a regularization operator to compensate for sudden changes in amplitude along events with an expected dip. Accomplishing this in the CRP planes requires some interpretation of the result of migration, but along the phx we expect the events to be flat and horizontal as long as the correct velocities have been used for imaging. In this paper, to keep A simple, we will just be applying the steering filters horizontally along the phx axis. This regularization scheme will minimize changes in amplitude along the phx axis, penalizing large amplitude changes the most.