  Recently multiscale imaging approaches such as DoG-HiT were developed to
solve the VLBI imaging problem and showed a promising performance: they are
fast, accurate, unbiased and automatic. We extend the multiscalar imaging
approach to polarimetric imaging, reconstructions of dynamically evolving
sources and finally to dynamic polarimetric reconstructions. These extensions
(mr-support imaging) utilize a multiscalar approach. The time-averaged Stokes I
image is decomposed by a wavelet transform into single subbands. We use the set
of statistically significant wavelet coefficients, the multiresolution support,
computed by DoG-HiT as a prior in a constrained minimization manner: we fit the
single-frame (polarimetric) observables by only varying the coefficients in the
multiresolution support. The EHT is a VLBI array imaging supermassive black
holes. We demonstrate on synthetic data that mr-support imaging offers ample
regularization and is able to recover simple geometric dynamics at the horizon
scale in a typical EHT setup. The approach is relatively lightweight, fast and
largely automatic and data driven. The ngEHT is a planned extension of the EHT
designed to recover movies at the event horizon scales of a supermassive black
hole. We benchmark the performance of mr-support imaging for the denser ngEHT
configuration demonstrating the major improvements the additional ngEHT
antennas will bring to dynamic, polarimetric reconstructions. Current and
upcoming instruments offer the observational possibility to do polarimetric
imaging of dynamically evolving structural patterns with highest spatial and
temporal resolution. State-of-the-art dynamic reconstruction methods can
capture this motion with a range of temporal regularizers and priors. With this
work, we add an additional, simpler regularizer to the list: constraining the
reconstruction to the multiresolution support.
