Extreme background problems after Wipe

[whixson]

Did an RGB of the Eyes Galaxies over Seattle. 9 3-minute subs. Here's what the output was after crop, aggressive Wipe, and Autodev. What went wrong?

NGC4435-RGB.jpg (505.32 KiB) Viewed 5168 times

[ecuador]

What happens if you do a ROI autodev (drag a rectangle around one galaxy)?

[whixson]

Doesn't make much difference. I imagine it's the light pollution here near Seattle that's causing all that colored confetti? Maybe more shorter exposures might help to tame it.

[admin]

That's some pretty extreme noise... How did you stack this? Would you be able to upload the stack?

[whixson]

That's some pretty extreme noise... How did you stack this? Would you be able to upload the stack?

Here's a link to a dropbox folder with the stacked image NGC4435.fit and the individual images. Captured and stacked in MaximDL. I've since corrected the donut-shaped pollution, was a blotch on the rear cell of my telescope. But I still have the same noise problem even after.

3 minute RGB subes, QSI 690 at -20 degrees, Televue NP127is.

https://db.tt/dACPwMvk

[admin]

Wow, you got some gnarly gradients in there... Some flats would really help.

As for the noise (which is made visible by AutoDev), that's unfortunately simply down to not having enough subs while shooting under light polluted skies.

Note that use of AutoDev when the object(s) are small and otherwise reside on an "empty" background require the use of an RoI (over one of the galaxies for example). You will be able to get a good global stretch that doesn't bring out the noise.
From the AutoDev content;

Usage

AutoDev has a lot of smarts behind it - some heavy analysis is going on of the ROI so that it can find the optimum histogram transformation curve. Develop, in comparison, is rather 'dumb' and mimics photographic film development, which doesn't actually take into account what is in the image.

Understanding AutoDev is pretty simple really; its job is to look at what's in your image and to make sure as much as possible is visible. The problem with a histogram transformation curve (aka 'global stretch') is that it affects all pixels in the image. So, what works in one area (bringing out detail in the background), may not necessarily work in another (may make a medium-brightness DSO core harder to see). Therefore stretching the image is always a compromise (fortunately we have other tools to 'rescue' all the detail liek Contrast, HDR, etc.). AutoDev finds the best compromise, given what detail is visible in your image

The latter is a really useful feature, as it is also very adept at finding artefacts or stuff in your image that is not real detail but requires attention. That's why it's almost always the first thing I do after loading an image - to see what we're working with. AutoDev will show it, warts and all.

After fixing the warts, we can start using AutoDev's skills for showing the remaining (this time 'real') detail in the image.

If most of the image consists of a background and just a small object of interest, by default AutoDev will weigh the importance of the background higher (since it covers a much larger part of the image vs the object); given what it has to work with it's the best compromise. If the background is noisy, it will start digging out the noise, mistaking it for fine detail. If this behaviour is undesirable, there are a couple of things you can do in AutoDev.

1. Change the 'Ignore Detail <' parameter, so that AutoDev will no longer detect fine detail (such as noise grain).
2. Simply tell it what it should focus on instead by specifying an ROI and not regard the area outside the ROI just a little bit ('Outside ROI influence').

You'll find that, as you include more background around the object, AutoDev, as expected, starts to optimise more and more for the background and less for the object; it's doing its job very well!

So, to use the ROI effectively, give it a 'sample' of the important bit of the image. This can be a whole object, or it can be just a slice of the object that is a good representation of what's going on in the object in terms of detail, for example a slice of a galaxy from the core, through the dust lanes, to the faint outer arms.

There is no shame in trying a few different ROIs in order to find one you're happy with. What ever the case, it certainly beats pulling histogram curves, both in results and objectivity (you've got a dedicated algorithm/assistant watching over your shoulder!).