  In this work, we propose a new discretization for second-order total
generalized variation (TGV) with some distinct properties compared to existing
discrete formulations. The introduced model is based on same design principles
as Condat's discrete total variation model (\textit{SIAM J. Imaging Sci}.,
10(3), 1258--1290, 2017) and shares its benefits, in particular, improved
quality for the solution of imaging problems. An algorithm for image denoising
with second-order TGV using the new discretization is proposed. Numerical
results obtained with this algorithm demonstrate the discretization's
advantages. Moreover, in order to compare invariance properties of the new
model, an algorithm for calculating the TGV value with respect to the new
discretization model is given.
