These algorithms, and the development shown on
this paper in particular, are extremely interesting. Despite the fact that these algorithms are very intensive and require GPU-based implementations to be feasible, an implementation on PixInsight would be certainly possible. Our C++ development platform is mature and more than sufficient to host a project like this. GPU support can be implemented for specific tasks by linking a PixInsight module with the required external libraries. The advantage of a PixInsight implementation is the availability of a rich, stable and powerful multiplatform infrastructure. PixInsight modules can be released as open source or closed source, free or commercial products. Our development frameworks are released as
open source under a liberal
BSD-like license that allows practically everything.
However, unfortunately, don't expect this to happen. The probability of a group of academic people being interested in PixInsight is basically zero. I am unable to implement something like this, mainly because it is probably beyond my technical capabilities, and even if I were able to manage the difficulties of such a complex project, this is something that I cannot afford. There are much more important things that must be done, including urgent tasks required to keep PixInsight alive and able to compete, and I am completely alone to do everything. So this is just impossible from any practical point of view.
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Unless you see this error message again or detect a repeatable pattern, just don't care about it. Things that happen.