Satellite trails appear as long lines in astronomical imaging, often nearly unresolved or slightly resolved. They are easy to find, fit, and subtract away, at least in principle. I have had several undergraduate researchers, however, who got close but couldn't deliver a robust, reliable piece of code.
The code I imagine takes an image (and an optional inverse variance image). It identifies if the image contains a satellite trail (possibly using the Hough Transform and some heuristics). If it does, it fits the trail using robust fitting techniques. If that all works, it returns to the user an updated image and an updated inverse variance map. Not hard! The only hard parts are making it robust and making it fast. I have a lot of good ideas on both parts of that; I think this is very do-able, and it is only a few weeks work for the right person. It would be hella useful too, especially for the human-viewable image projects I am working on. Enhanced goal: Fit for satellite tumbling or blinking (both things are common in the data I have).