What is up with Astro-Pixel Processor team? Aries Productions Astro Pixel Processor (APP) · Rajat Kumar · ... · 35 · 1773 · 0

ONikkinen 4.79
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Timothy Martin:
Oskari Nikkinen:
Stacking stacks is the least effective way of handling data in my opinion because you dont get as good a result as when stacking all the subs into one image. Its just a math thing, averaging 4 averages is not the same as averaging all the subs once (latter is better, significantly).

I see the session thing as a weakness in the software. Really calibration and stacking are two different things done at different times. Calibration happens after the imaging night and then those subs get stored for later use. Stacking happens after any number of nights, which could be months after calibration. The "black box" design of APP discourages the user to take this approach IMO.

Sub rejection rates also have nothing to do with the stacking software used. You select the method and limits of rejection and stack the frames you want - at least thats what is supposed to happen.

You can very easily save calibrated frames in APP. There’s a button in the Calibration tab to do that. Then you can stack them later with frames calibrated in prior sessions.

There’s no question PI has the better UI. If only its results were better, I’d use it.

Yes i can do that but why would i ever calibrate data in APP? It takes at least 5 times longer than with Siril, and the results are actually much worse since APP refuses to use a darkflat i had supplied. And on that note APP refuses to work with images that were calibrated in any other software so its not good for just stacking either.

What problem are you having with PI stacking results? Stacking results should be exactly the same from every software, unless there was an error in how that software was used because at the end of the day its just averaging normalized and registered subs with outlier rejection - so just math. Unless the math is done wrong by one software then all the results will look the same.
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AccidentalAstronomers 18.64
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Oskari Nikkinen:
What problem are you having with PI stacking results? Stacking results should be exactly the same from every software


Lol. If that were true, then every NASCAR race would be 40-way tie.
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CCDnOES 8.34
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DavesView:
The major problem I have with WBPP is multi-nights. There is entirely too much file management with it and for someone in their 70s who sometimes can't remember why I walked into a room, moving files around and keeping it all straight in my head is a PITA.

Really? I am also in my 70s and I use neither APP or WBPP. Too much "black box"  for my taste. I manage my files and perform each calibration step separately in PI like in the old days. That way I know precisely what is done for each step and do not rely on setting up WBPP to get everything done in the way I had intended.  Doing that is sometimes more work and more error prone than manual calibration. It is a matter of what works for you and that works for me.

As far as forgetting why you entered a room? That is not related to age (at least most likely it is not). It is called the "doorway effect" and is simply a result of the way the brain works. BBC had a good short explanation of the effect:

Doorway Effect
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PhotonPhanatic 4.53
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DavesView:
The major problem I have with WBPP is multi-nights. There is entirely too much file management with it and for someone in their 70s who sometimes can't remember why I walked into a room, moving files around and keeping it all straight in my head is a PITA. APP's multisession approach is much more desirable.


Actually, I just learned that WBPP handles multi-nights pretty easily. Adam Block explains it in a couple of the videos in his extensive tutorial on WBPP. Take a look at this video, for example:

https://youtu.be/KfjkLUXuwCI?si=WZeyEBw8wX_p1E04

I managed to set up NINA so that it stores the various subs (lights/darks/flats/etc.) for a target over multiple nights in a folder structure that is precisely what WBPP expects.

Full disclosure: I'm in my 60's and I also frequently forget why I walk into a room. :-)

(also: no disrespect intended to APP. I've never used it. Thought I'd share what I had learned about WBPP since it came up in the thread, in case it was helpful for anyone.)
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DavesView 2.39
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Bill McLaughlin:
As far as forgetting why you entered a room? It is called the "doorway effect".

It's also called a joke... sometimes.

Bill McLaughlin:
I manage my files and perform each calibration step separately in PI like in the old days.


You mean like with 2 cans and some string? 🤣
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mrkhagol 2.71
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I stopped usign APP 2 yrs back I think once realized that Siril can do better and faster.

APP was always hit and miss and never got the results I wanted.

Just start using Siril (and Pixinsight as well)-which will go a long way.

PXS can do more than Siril but it's an uphill climb to know everything about PXS and do it very well.
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CCDnOES 8.34
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DavesView:
You mean like with 2 cans and some string? 🤣


Perhaps - but I think I will let the results speak.
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DavesView 2.39
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Bill McLaughlin:
Perhaps - but I think I will let the results speak.

I've seen your images. No doubt you turn out excellent product. Just funning. Your understanding of this stuff far outweighs mine, so I often use the tools that others create because I'm just not that good at it.
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CCDnOES 8.34
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DavesView:
I've seen your images. No doubt you turn out excellent product.


I wish it was a product. Then I could finance more equipment! 

As it is, amateur images have basically no economic value and fit the oft used description of: "with that and $5 you can buy a cup of coffee". 

I once had an insurance agent tell me I needed a commercial policy for my astronomy equipment because I had sold a couple images (this was way back in the early 2000's). I told her what I got for the images and what the equipment cost.  That was the end of that discussion. 

I suppose there are a few that have been able to turn their hobby into a business but I suspect there are far more failures at that than there are successes.
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dkamen 7.44
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Oskari Nikkinen:
Stacking stacks is the least effective way of handling data in my opinion because you dont get as good a result as when stacking all the subs into one image. Its just a math thing, averaging 4 averages is not the same as averaging all the subs once (latter is better, significantly).

Hi,

If every average represents the same number of subs and there is no multiplicative or nonlinear treatment then average of averages and average once are exactly the same. 

It is when you introduce weighting, normalizarion and rejection that things become different. But it is not at all certain the average of averages will do worse.

Take the following 4 scenaria in a high light pollution and relatively wide fieldsituation:
1) stack each night, do gradient removal on each stack, stack the stacks
2) do gradient removal on every sub, stack once
3) stack once, do gradient removal on the result
4) stack the stacks, do gradient removal on the result.

I find that 1 produces the best result by far, followed by 3. 2 gives bad SNR and bad gradient removal because signal is too weak for accurate gradient modeling. 4 produces the worst results (very wild gradients, very difficult to remove).

Interestingly IIRC the APP team recommends 4. Maybe they have much darker locations in mind.

Cheers,
Dimitris
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whwang 15.16
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I agree with Dimitirs.  Mathematically, averaging averages is exactly the same as averaging everything all at once, even with weighting (but you, or the program, need to handle weights correctly).

The obvious advantage of stacking everything at once is that this gives you more subs for more efficient outlier rejection and more efficient drizzling.  But if each of your separate stacks contain sufficient number of subs, you don't need to worry about this.

Regarding gradient removal, if you have multiple sessions from multiple nights with different conditions, the subs can have very different gradients.  If you stack them all at once, the mix of many different gradients can become a highly complex gradient in the final stack (Dimitris' method #4).  This will make gradient removal highly challenging and problematic.  Stacking each session separately and doing gradient removal on the stacks before the final stack (Dimitris' #1) can mitigate this. Another way to overcome this is to run PI's local normalization (or John Murphy's nomalizescalegradient script) on each sub before stacking.  This will force the gradient in each sub to match the gradient in the reference sub, and avoids a complex gradient in the final stack.  This doesn't suffer from the low S/N issue mentioned by Dimitris because technically this isn't gradient removal.
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