  Reconstructing images from ill-posed inverse problems often utilizes total
variation regularization in order to recover discontinuities in the data while
also removing noise and other artifacts. Total variation regularization has
been successful in recovering images for (noisy) Abel transformed data, where
object boundaries and data support will lead to sharp edges in the
reconstructed image. In this work, we analyze the behavior of BV solutions to
the Abel inverse problem, deriving a priori estimates on the recovery. In
particular, we provide L2-stability bounds on BV solutions to the Abel inverse
problem. These bounds yield error estimates on images reconstructed from a
proposed total variation regularized minimization problem.
