inFINNity Deck

Hi geoflewis, Nice image! What scope and camera dis you use? Nicolàs

Hi Peter, If you are using the advanced sequencer, you will need to add a park scope at the end of it. HTH, Nicolàs

Hi Jamie, try this one: https://www.astro.rug.nl/~gaia/ I have never worked with it, but I think this is what you need. HTH, Nicolàs

Hi Alan, thanks for linking to my article. Yesterday, as a result of the discussion in this planetary imaging thread, I have published a second article on that Dutch forum in which I dive deeper into that matter and comparing my method, which was based on being able to solve a Rayleigh-object, with the method @vlaiv used (based on the Spatial Cut-off Frequency) and to my method but then based on the Sparrow and Dawes criteria. The differences between the four methods are small (as calculated for 540nm): Sparrow-criterion: 3.9 x |px| Spatial Cut-off Frequency: 3.7 x |px| Dawes-criterion: 3.6 x |px| Rayleigh-criterion: 3.0 x |px| That these differences exist is due to the detail level that is resolved. The Rayleigh-criterion is not yet on the limit (the combined intensities of two objects still shows a dip in between). With the Dawes-criterion there is no visual dip, while at the Sparrow-criterion there is no mathematical dip. In practise our images are affected by aberration, lack of contrast and seeing causing the images to become oversampled (i.e. the worse the seeing, the lower we can choose the factor before we are oversampling). For this I added a section explaining how Fiji can be used to test whether our images are under- or oversampled (as kindly explained by @vlaiv to me, for which I am grateful), which shows that especially seeing has a significant effect on oversampling as a result of which the factor of 3.0 still is safe to use (in most, if not all, situations oversampling will still occur at this level). The article can be found here: https://www.starry-night.nl/vergroting-onder-de-loep-deel-2-het-optimale-f-getal-nader-beschouwd/ Opening it in Chrome should translate it. Nicolàs

What was left to test, is how seeing affects the frequency spectrum. For this I have taken three images from the article in which Siebren van der Werf and I discuss the effect of seeing and aperture on the visibility of sunspots (or other small detail). The three images are produced for a C11 at f/10 with a 2.95 micron camera to which a convolution of Gaussian seeing and Fraunhofer diffraction is applied (as per our article). From left to right they represent perfect seeing (i.e. no seeing, only Fraunhofer diffraction applied), 1" seeing and 2" second seeing and with seeing defined as 2 sigma (some seeing measurement-systems use 2.355 sigma). As can be seen, and as expected, the seeing has a dramatic effect on the frequency distribution, doubling the oversampling per arc-second seeing (I am surprised to see that the first image is already oversampled by a factor of 2, but that is most likely due to the image that was used as input). Of course these represent single images as one would capture under these circumstances, stacking would improve the result. Nicolàs

Same exercise for pink noise (crop of one of the frames of the video on this page) : Nicolàs

So, time for a little test... I took an image of white noise from WikiPedia and made two copies of it: the first one twice the canvas size, but with the original image centred in it on a black background (thus still original sampling), the second by resizing the original image with smart resize in Paint Shop Pro (thus oversampled by a factor of 2). Those three images then were processed in Fiji using the FFTJ plug-in: The top row shows the three images, the bottom row the frequency spectra. At the lower left I made a copy of the left spectrum to indicate two dark regions that can be seen in all three spectra (is the original image truly white noise then?). Adding more canvas causes FFTJ to enlarge the output image and to stretch the frequency response over the canvas (the two dark regions a further apart), as a result of which the whole image is filled with data (and as a bonus we get a central cross due to the black background). Resizing the original image by 200% causes FFTJ to enlarge the output canvas, but the frequency response remains the original size (we can see the two dark regions on their original places). So, indeed oversampling is detected by this method. This leaves us with the question why the greyscale version of my Jupiter image results in such a different response when compared to the green channel, I guess it is due to all the processing steps I did (LRGB combine in WinJupos, saturation in PSP and denoise in Topaz AI). Nicolàs

I took the original G-channel and did analysis on that without cropping: I can see at least three areas: the centre, then a narrow darker region, followed by a broader and brighter one (I may have drawn it slightly too small). It appears as if in the far corners the signal get stronger again, which could be even a fourth area of signal/noise. So, if the corners still contain signal instead of noise, then the image is undersampled at f/20, otherwise it would be oversampled (which I think it is). That would be a great experiment, but sadly enough not feasible from my observatory. Nicolàs

Hi Vladimir, here are the frequency spectra of my recording: At the left the original recording, at the right the 200% resized version. I think it shows that at f/20 my set-up is not far off the optimum sampling rate. The camera has 5.9 micron pixels. According to my approach this should require a 5.9 x 3 = f/17.7 scope, according to yours 5.9 x 4 = f/23.6. So my f/20 set-up seems to be somewhere in between the two methods of calculating the correct focal ratio. Can you please comment on this? Nicolàs

Hi Vladimir, thanks for explaining, managed to reproduce your results using FFTJ on the green channel in a 512x512px crop: And this is when that green layer is reduced to 25%: Indeed the oversampling seems to be a bit less than 4x. Nicolàs

Hi Vladimir, this is quite an interesting thread! Regarding your above question I tend to resize my planetary images by 200% after processing mainly as it is easier to see the details (especially because I am presbyopic 🤓) and a bit because of c). So here is my latest Jupiter with C11 @ f/20 using a TeleVue 2x PowerMate, ZWO ADC, ZWO LRGB filters and a ZWO ASI174MM (5.9 micron pixels). The animation is the size as captured: I think this is about the best we can expect from a C11 EdgeHD, only even better seeing may improve things (marginally). The best frame of this set I then resized by 200% to make the details stand out a bit more: Obviously this is severely oversampled now and by nowhere as detailed as the images shown above. Now, the reason I show this is that I tried to do this Frequency analysis you showed us above using Fiji's plugin FFTJ (both with my own images and that of Chris Go), but have trouble arriving at the same results as you did, although it appears that Chris's image is oversampled by a factor 4. Could you please explain the steps you took? What I did is as follows: - downloaded the full 4-Jupiter image - cropped it to 862 x 812 pixels to only contain Chris's image - made it greyscale - loaded it in Fiji - Using the FFTJ plugin generated a forward transformation at double precision - Generated a Show Frequency Spectrum (logarithmic) at Volume-Center - stretched it by clicking Auto several times (until maximum is reached) in the Brightness/Contrast function: But as you can see I get a very different result, but, being a novice in Fiji/ImageJ, I take it I must be doing something wrong. 🤔 Nicolàs

I agree if the base is already done, then there is little options left, so then it indeed is your last resort.... Nicolàs

I see that you have fixated the batons both to the outer slab and to the central concrete square on which the pillar stands. This more or less nullifies the effect of having those two parts separately pored. Why not creating a framework that does not touch the central concrete? Nicolàs

Silicon should only be used as a last resort as there is a fair chance that it will start leaking again after some time. Better to avoid water can ingress at all. Nicolàs

Dear Nigella, Actually It should not matter as it looks at stars at an almost infinite distance, so a few centimetres left or right cannot affect its functioning. Therefore it is best to choose the most sturdy and convenient orientation, which seems to be the first image. HTH, Nicolàs

Hi Dogstar, good to see you found my drawing, which I posted a while ago here. The circular rims can be made from thin plywood, if needed multiple layers, of from a plastic like HDPE, which can be sourced in various thickness. Even at 20mm thick HDPE bends quite easily. Nicolàs

Hi Reeny, to me it looks like your image was not taken at the sweet spot of your etalon. This sweet spot is explained here: https://solarchatforum.com/viewtopic.php?t=30881 And here I explain one way how to deal with it: HTH, Nicolàs

Hi Onikkinen, Thanks for showing a bit of raw data, that already looked pretty good. Nicolàs

Hi Onikkinen, that is an amazing animation! I presume you used a barlow in the process? Could you share a short video of the data you collected, so we can see what Jupiter looked like when you were recording it? Thanks, Nicolàs

Stunning image! I had to look up your location and found out that it is 'only' a Bortle 2 sky. Not jealous at all, being in Bortle 5/6 myself.... 😉 Nicolàs

it was mainly due to the atmospheric conditions. As a matter of fact, I did not expect any data from that session as the seeing was not great. In the end it turned out pretty reasonable and as I prefer not to over-process the images, I left it as it is. Nicolàs

Hi Robin, you're absolutely right, I did not express myself properly.🤔 Indeed a larger barlow distributes the light differently. If one goes from a 2x barlow to a 4x barlow, the planet will appear twice as big on the chip and the amount of light per pixel will therefore be a quarter of what it was. Binning could be done, but then we are back to where we started, so is rather pointless (unless no smaller barlow is available). Examples of my imaging: Sun with Lunt @ 3.7 x [pixel size] Jupiter with C11 @ 3.4 x [pixel size] and 200% resize Mars with C11 @ 3.4 x [pixel size] and 200% resize Nicolàs

The ADC will shift the focal point by about 34% of the glass thickness, just as your filters and camera-window will do. Now, I have never dismantled an ADC, so have to guess the glass-thickness, could be as much as 3mm per wedge, making the focal point to shift outwards by about 2 x 0.34 x 3 = 2mm. In below drawing n is the breaking index of glass, which is about 1.5168 for Schott N-BK7 glass: The ASI224 has a 3.75 micron pixel size, so optimum focal ratio would be 3 x 3.75 = f/11.25, although, thanks to stacking, good results are achieved when going higher than that (e.g. 4-5 x 3.75 = f/15 - f/18.75. The nice thing about that is that the image will be larger on the chip (and thus on your screen later), the downside is that it costs light (quadratic to the increase in focal length), so exposure times go up. With my C11 I usually image at 3.4 x [pixel size] and then bicubic resize the image if I want it to be larger. With my Lunt I usually image at 3.7 x [pixel size] without resizing. Nicolàs

You can test whether it is caused by pinched optics or by screws or spacers in the light path by applying an aperture mask. A reduction in aperture of about 4mm should suffice. Try to make the opening as smooth as possible as any deviation from a perfect circle will add new spikes. If the pattern is caused by pinched optics, the make-shift aperture mask will only add more spikes, but not remove the ones you already have. If caused by screws or spacers in the light path, the three large dark spikes should be gone (and replaced by irregular spaced new ones from the mask). I had similar issues with an Esprit 80ED, which I solved using a 79mm aluminium aperture mask, see this Dutch thread (opening in Chrome should translate it): https://www.starry-night.nl/het-verwijderen-van-artefacten-bij-een-refractor-met-een-brilletje/ Nicolàs

ok, so that would make focal length either 1071.3mm or 1070.4mm, which we can round to 1071mm (provided above dimensions are correct). At least this provides tomato (not his real name I presume?) with a direction. Lettuce (aka Nicolàs)