Most geophysical problem require some type of regularization. Unfortunately most regularization schemes produce ``smeared'' results that are often undesirable when applying other criteria (such as geologic feasibility). By forming regularization operators in terms of recursive steering filters, built from a priori information sources, we can efficiently guide the solution towards a more appealing form. The steering methodology proves effective in interpolating low frequency functions, such as velocity, but performs poorly when encountering multiple dips and high frequency data. Preliminary results using steering filters for regularization in tomography problems are encouraging.