Niall, I think Emanuele was concerned on the seamless part, not the matching of the images
The usual approach is to build masks, and then use PixelMath to replace data (or average). One way to create such mask is to binarize one of them (I suggest the longer one., which I suppose fits enterely inside the shoft f frame), so all the signal is white and leave black the areas without signal. Then, use the minimum filter to "expand" the black area, with a low amount, so you'll create some sort of gradient.
Now, before applying the image, use the new LinearFit process to match both images. Then, using the mask on the short f frame, replace its contents with the image of long f (just put the name of the image in PixelMath). The mask will act a a linear "interpolation". This should work.
Another alternative is to try Georg's script for seamless mosaicing. Basically, it merges the images at the gradient domain, and then recovers the merged result. It should give better results, in terms of the seam, but right now the algorithm has several limitations. Anyway, it is worth a try.