  The advent of enhanced technologies in radio interferometry and the
perspective of the SKA telescope bring new challenges in image reconstruction.
One of these challenges is the spatio-spectral reconstruction of large
(Terabytes) data cubes with high fidelity. This contribution proposes an
alternative implementation of one such 3D prototype algorithm, MUFFIN
(MUlti-Frequency image reconstruction For radio INterferometry), which combines
spatial and spectral analysis priors. Using a recently proposed primal dual
algorithm, this new version of MUFFIN allows a parallel implementation where
computationally intensive steps are split by spectral channels. This
parallelization allows to implement computationally demanding translation
invariant wavelet transforms (IUWT), as opposed to the union of bases used
previously. This alternative implementation is important as it opens the
possibility of comparing these efficient dictionaries, and others, in
spatio-spectral reconstruction. Numerical results show that the IUWT-based
version can be successfully implemented at large scale with performances
comparable to union of bases.
