  In this paper we propose a new approach for tomographic reconstruction with
spatially varying regularization parameter. Our work is based on the SA-TV
image restoration model proposed in [3] where an automated parameter selection
rule for spatially varying parameter has been proposed. Their parameter
selection rule, however, only applies if measured imaging data are defined in
image domain, e.g. for image denoising and image deblurring problems. By
introducing an auxiliary variable in their model we show here that this idea
can indeed by extended to general inverse imaging problems such as tomographic
reconstruction where measurements are not in image domain. We demonstrate the
validity of the proposed approach and its effectiveness for computed tomography
reconstruction, delivering reconstruction results that are significantly
improved compared the state-of-the-art.
