  L2-TGV-regularization has been introduced by Bredies, Kunisch, and Pock. This
regularization method requires careful tuning of two regularization parameters.
The focus of this paper is to derive analytical results, which allow for
characterizing parameter settings, which make this method in fact different
from L2-TV (the ROF-model) and L2-TV2 regularization, respectively. In this
paper we also provide explicit solutions of TGV-denoising for particular
one-dimensional function data.
