  We have developed a novel method for co-adding multiple under-sampled images
that combines the iteratively reweighted least squares and divide-and-conquer
algorithms. Our approach not only allows for the anti-aliasing of the images
but also enables PSF deconvolution, resulting in enhanced restoration of
extended sources, the highest PSNR, and reduced ringing artefacts. To test our
method, we conducted numerical simulations that replicated observation runs of
the CSST/VST telescope and compared our results to those obtained using
previous algorithms. The simulation showed that our method outperforms previous
approaches in several ways, such as restoring the profile of extended sources
and minimizing ringing artefacts. Additionally, because our method relies on
the inherent advantages of least squares fitting, it is more versatile and does
not depend on the local uniformity hypothesis for the PSF. However, the new
method consumes much more computation than the other approaches.
