Way back at the time PI v1.1 was released, there was the following quote from Juan :

- FourierTransform process. The idea behind this tool is quite simple, but powerful: transform an image into the frequency (Fourier) domain, and provide a graphical interface to edit the Fourier transform, including pixel drawing tools. Then perform the inverse FFT, back to the spatial domain. An ideal tool to handle periodic image features, as interferences or repetitive textures and patterns.

Am I missing something obvious (BTW, I am not near my PI install, so I can't check), but do we now have an FFT Process, or is this something still 'in the pipeline' ?

The reason I am asking is that I would like to have a look at my Flat subs, and my MasterFlats after FFT, specifically to see whether there is any residual 'regular pattern' present, the existence of which would leave me considering 'why', and 'what next' as far as Flats acquisition was concerned. (The same analyisis might also show interesting results when applied to Darks, FlatDarks and Offsets, of course)

This follows on from a discussion I had here on the Forum with Simon Hicks, who pointed out that, just because my MasterFlat showed almost 'zero' Standard Deviation, this would not necessarily mean that the 'minimal' distribution of ADU values on the image didn't in fact have some sort of 'pattern' associated with it. For example, consider an image with ADU values that were either '1000' or '1001'. Now, a simple statistical analysis would show a very narrow 'peak', centred around a Median value of '1000.5'. However, the '1000' values might represent the 'every ODD line', and the '1000.5' values might represent 'every EVEN line'. In other words, an image with a very obvious spatial pattern (trivial in this case, as it would be easily observed with a suitable STF for example), and one that would produce a very obvious result in the FFT domain. However, a 'true' MasterFlat, with no anomalies other than vignetting gradients and 'dust donuts', would not show the FFT 'spikes' associated with regular frequencies.

Hopefully, if I understand the concept of FFT correctly, if there is no obvious 'pattern' in the FFT domain, then the source image probably does NOT have any regular spatial patterning.

Of course, my interpretation may be completely flawed - but that is why I want to 'play' with my data and an FFT Process in the first place

Cheers,