  The Sunyaev-Zel'dovich effect is the ideal probe for investigating the
outskirts of galaxy clusters. To map this signal, we apply a spectral imaging
technique which combines parametric component separation and sparse
representations. Our procedure is an improved version of an existing algorithm,
which now features a better treatment of astrophysical contaminants, and the
implementation of a new beam deconvolution. We use the most recent frequency
maps delivered by \textsl{Planck}, and we consider the clusters analysed in the
\textsl{XMM} Cluster Outskirts Project (X-COP). In particular, we focus on the
images of two clusters which may be possibly interacting with neighbouring
objects, namely A2029 and RXCJ1825. We also highlight the advantages of the new
beam deconvolution method, through a comparison with the original version of
the imaging algorithm.
