vlaiv

ImageJ. I tried many, I even downloaded evaluation copy of PI, but I never warmed up to it. ImageJ allows me freedom not many other software does. It is built for completely different purpose - scientific image processing for microscopy - that was original goal. It has most of the functionality you'll need to calibrate, align and stack your data out of the box - but it also lets you program additional features in form of macro language or plugins. It will probably be completely useless for most novice users, but if you have background in programming / image and signal processing - then it is valuable tool box. I've written several plugins of my own that I use when stacking and processing data. As far as I can see - Siril will do important part of the job for me, and I plan to include it in my workflow. One of the problems with ImageJ that I have now is that I can't do automatic alignment in the way I would like to do. There is really nice plugin that uses RANSAC algorithm to do frame alignment - but it either produces transform matrix or performs actual alignment using bilinear interpolation. If you want better interpolation algorithm - you need to manually align subs using that transform matrix and different plugin. I also written plugin that uses Lanczos interpolation - but that was just to test out things - I did not code it to be fully functional alignment plugin (like load matrix data and align all subs). Due to work and other commitments, I don't have much time now to implement that - but hopefully I'll make software for stacking at some time in future - I have several very interesting and innovative algorithms that I tried out using ImageJ. I've written couple of times about these ideas and presented results. For example here: That one deals with different quality of subs in the way no other stacking software does. Most just assign "weight" to whole sub - but there is no single weight that is appropriate for whole sub (there is no single SNR for whole image - every pixel has its own SNR) - each portion of sub requires different weight depending on SNR of that particular part of the image - my algorithm deals with that and breaks image up in zones depending on SNR and assigns weight according to SNR of each sub compared to others.

There you go - Lanczos-4 will do Must download latest version of Siril - I have old one that I tried some quite a bit long time ago.

That depends on their speed in flight

I don't really have favorite, but I dislike using DSS because it uses simple bilinear interpolation which alters noise statistics and lowers resolution in the image - acts as strong low pass filter. As long as it is decent filter - like Lanczos, Splines of higher order - is better than simple bilinear / bicubic filter You can see that image has been stacked with DSS if you examine noise grain. Here is simple comparison to show you what I mean: From left to right - just some Gaussian noise in first image, second image is first image translated by 0.5px, 0.5px using bilinear interpolation, third image is again - first image translated by 0.5px, 0.5px - using Quintic B-Spline as interpolation. You can clearly see blur that results from use of bilinear interpolation. It not only impacts noise in the image - but also detail. FWHM of stars increases after registration with bilinear interpolation.

Do you know what interpolation algorithm is used for registration (does it have a choice)?

Good thing this is in Imaging section and not Getting started with imaging

I was just quoting wiki in changed form as per Olly's comment about difference between wildebeest and gnu: Species of black wildebeest actually mentions Gnu in Latin while Blue wildebeest, although same genus is another species.

Gnu is not blue!

As first step - try doing what I suggested - use larger alignment point and deal with field rotation. For next session - check if you can set quality of images in your camera / quality of Jpeg. There is often option to select between file size and quality of image - use highest quality setting to minimize artifacts. Some cameras have hacks that enable saving of raw images instead of compressed. Canon range of compact cameras (non DSLR type cameras) has something called CHDK that you can use to obtain more control over camera. https://chdk.fandom.com/wiki/CHDK Maybe Nikon has something similar? If not, then alternative will always be to purchase second hand DSLR type camera for this purpose and use it with lens or scope to get raw files. When I first started doing planetary shots - I used modified web camera - and had issues with compression, however, I was able to get at least some results. Switching to camera with raw output really improved things.

Point of stacking is to reduce noise (or rather improve Signal to Noise Ratio - SNR, sometimes written as S/N). Actual exposures used for lucky type lunar images are 1/250 - 1/500 range (few milliseconds). Individual frames are very noisy, but once you stack couple hundred of them - SNR improves and you get very smooth image that can be sharpened well. Another thing that you should not worry about is if your individual shot is a bit darker - you don't need to properly expose it, that is another thing stacking does for you - it creates very high dynamic range and you can brighten image later.

I'm not sure what would be the best course of action in this case as I haven't used it like that (it won't produce nice results because of compression). First thing that you should try is to set alignment point to larger size - maybe try 104 or 200 pixels in size. One that you are using is too small and will pick up individual compression artifacts and just amplify them (it will not align on lunar features but rather on compression artifacts). Once you do that, I'm afraid you won't be able to sharpen much as sharpening will again bring out that blockiness in the image - but give it a go anyway and see what you can get (here I mean for example Registax wavelet routine for sharpening). Another thing is to stack only best 10% of frames (not sure how many frames you have in total). Since you are using stationary / not tracking mount - there is field rotation. AS!3 is capable of dealing with that, but you need to turn it on. there is section with field rotation parameters: You need to know your location and time of recording - first / last frame and enable field derotation.

Hi and welcome to SGL. It looks like you are using video format that has a lot of compression. Those squares are very indicative of Jpeg type compression at very high settings, so codec used might be Mpeg (which is just "motion" / video type jpeg). Info on the gear used would be very helpful in explaining this and also - if you could post single frame of those that you are trying to stack - for analysis.

Not sure if it is fair comparison. APP and PI are both capable of stacking the data and PS is full fledged image processing application. One could alternatively argue that Gimp is free - so even cheaper.

I would like to know "why" part as well

Indeed! House sized moon, come on, we all know that moon is roughly the size of football

It's only important if you start suffering from field curvature. Focal plane is really not flat plane at all. It is curved. This means that if center of the field is in focus - edges won't be and vice verse. How much defocus there will be - depends on how large your sensor is and how strong field curvature is. With small sensors in most cases you don't need field flattener as you can position sensor between two extremes - center stars will be slightly out of focus and corner stars will be slightly out of focus - but that out of focus blur is much smaller than for example seeing blur - and you don't see difference - stars look pin point enough both at center and at edges. If you have large sensor - like APS-C which has 27mm diagonal (that is almost double diagonal size compared to ASI533) then it is likely that you'll notice the effect and then field flattener is required in order to correct edge stars.

Such moon shots are perfectly "composable" by using proper kit and technique. Moon is far away enough not to be impacted by perspective and any house, building or mountain can be rendered arbitrarily small in frame - if we shoot it from far away. Here is example image that member of my local astronomy forum took: I cropped the image for effect, you can see whole of it here: https://ucb3cc45aa25f75d6af2e30af99f.dl.dropboxusercontent.com/cd/0/inline/BPSRIpezkERkr_bQE32kGrzpdAWV6v_e06kAuB8-myyj916cEtzDUdlHY2RszkW-1xRlk7kOJRcfHaobkufLug-O041BxN9thyXm-5P88ZuFIdD4SLegCOHGHJzJ3wQ7HOJJtoo-anFVT_MphGKPDgCi/file# However, that does not mean that people won't photoshop moon over their own house and post that on facebook or instagram.

That is excellent - and in no way lacking in comparison to our processing efforts.

I have no problem showing you some of the steps I took while processing this data. One part is a bit more involved - that is background removal. I use ImageJ and custom written plugin to do that. There are tools that you can use that will wipe background for you (like gradient Xterminator for PS that I've heard of but have not used it). In the mean time - to practice, I'll upload data that I wiped so you can use it. I binned your data x2 - as you are using OSC sensor and shooting with very restrictive filter. Only red and a bit of teal (OIII / 500nm) is passing thru - and there is not much data in green and blue channel: (this is R, G and B data from your image side by side - blue is almost non existent). Bayer matrix on sensor has every fourth pixel as red (RGGB 2x2 group of pixels) and there is not much point in having 3000x3000 image in mostly red color - you gain no detail by using such resolution. Data is also wiped / normalized: red.fitsblue.fitsgreen.fits You can now perform simple processing using Gimp for example (or PS - just use the same technique). Here is very simple 3 step level stretch, a bit of curves manipulation and some noise reduction: - Load channels and do RGB combine to get color image - Start by doing one round of levels - moving only top slider - move slider all the way down until you start clearly seeing nebulosity. This method will make all star cores bright and is not suitable if you want to retain star color - but it is very simple technique to use and it works good on image like this where star color is mostly lost due to filter used. so move top slider to the left - until you start seeing bright features of nebulosity - don't over expose / burn bright part of nebulosity though. Click ok. 2. Now we move middle slider in next step - we move it to the left again - this brings forward fainter parts of image but also raises background level (don't worry about that) Again click ok when happy. 3. You need to adjust black level on the image - raise left most slider up until the base of histogram. You can also set slightly higher output level - so that background does not look completely pitch black - that does not look good in images: 4. Put a bit more emphasis on nebulosity using curves now instead of levels like this: put one anchor at center of histogram so that this part does not move and use another adjustment point to the right so that you get nice sloping curve - adjust to your liking. 5. Do some noise reduction now. I use simple wavelets noise reduction - here is comparison - left side is unaltered and right has been denoised: Difference is obvious. You can also do masked denoise - only in dark parts (copy layer - denoise that, add layer mask with luminance as mask - bright parts should show original bottom layer, dark parts of mask should show denoised layer). Hope this gets you started in processing. You can also check out some videos on YouTube.

Hope you don't mind - I took the liberty to process your data more seriously and here is the result:

Ok, stack also shows that data is there and all is "fine": Problem is of course with light pollution and fact that stack has very high dynamic range - it needs to be highly stretched to show faint stuff. You have quite decent data - now you need to put effort into processing and learn how to best pull the image out of it. Above is just a quick manipulation in Gimp, if you wish, I can do a bit more serious processing of this data to see what I can pull out of it?

Good news is that it's not dew. Both first and last sub of the sequence show nebulosity clearly: Last sub has more LP - but that is probably due to direction of the target in the sky as it moves thru the night. I'll now inspect stack to see what it looks like.

Could you attach 3 things for inspection: - first raw frame of the night (without calibration) - last raw frame of the night (without calibration) - linear stack from DSS as 32bit fits format There might have been dew forming on your scope. That will ruin stacked image. If that is so - there will be significant difference between first and last frame (clear lens and dewed up lens).

Indeed - simple camera/lens with barn door tracker is very nice way to start. You can DIY EQ platform for your scope maybe? It is similar to barn door tracker used for cameras - except it is used for dob mounted telescopes. In either case - simple DC motor that runs off battery should be good for short exposures - and stepper motor with gearing will be more precise.

Before you do anything else - try binning your files a bit. DSS expects stars to be roughly round. Your stars appear ok when you look at them with reduced image size - but DSS looks at them at 100% zoom level, which means they look like this: DSS simply does not recognize those shapes as stars. If you reduce size of the image by binning (and improve SNR a bit) - it might be able to figure out that those are stars. You don't have to bin right away - you can simply reduce size to say 25% and try to see if DSS will stack images like that.