Help needed for a 1st timer with narrowband data.

[vlaiv]

5 minutes ago, Ryan_86 said:

Im not sure I could replicate that haha.

I'll post my workflow so you can try to replicate it, but there are some steps that I'm not sure you will be able to replicate directly - because I use custom written software, however steps are "general" and you seem to have right tools for them - namely background gradient removal / wipe.

First I'll try to see what sort of data I can get by different stacking tweaks and then I'll post workflow a bit later.

[vlaiv]

8 minutes ago, Ryan_86 said:

What do you guys think?

That Ha image looks very nice!

[Ryan_86]

That would be such a help  

I shall look forward to it.

Thanks for all your input Vlaiv

[vlaiv]

Ok, so here is result of my effort at data reduction (not sure if I can call it success ) :

Ha.fits

OIII.fits

SII.fits

Above are linear wiped 32bit stacks.

Here is RGB linear composition (with fairly aligned black points) - in 16 bit format (for those that can't work with 32bit formats):

sho-16bit.tiff

It's been linearly stretched (so it is still linear) to preserve dynamic range of data in 16 bits

Full RGB composition (SHO) in 32bit format (again fairly aligned black points):

sho.tiff

[vlaiv]

And here is how I process above data:

First I work on Ha that will be luminance, and first step is to do linear stretch just below saturation point - I use Gimp and levels for this:

Identify brightest part of target and move top slider until you hit place where any more movement to the left will saturate brightest part of target - you want to avoid saturating highlights.

Next step is really to ones liking - you want to adjust curves so that target is nicely exposed - I do it with round of levels by moving middle slider a bit and then using curves:

Now we need to do some clever denoising to make things smooth yet not too blurry.

To do that you create another layer - that one you denoise, I personally like wavelet denoising under G'MIC Qt filters in Gimp. After you have that denoised layer, you add layer mask to it - inverted value of that denoised image. This will blend more of denoised version in dark areas then in bright areas (mask will be inverted - where it is dark it will have higher value and apply more denoised version) - you can control overall contribution via mix slider (above is 77% of such denoised and masked layer on top of original).

Now it is time to process our color subs. We start by doing the same, but each channel we do separately, but this time don't try to push things overboard - start with first linear stretch and then stretch a bit more. Try to keep things "balanced" - about same brightness of each channel.

Do RGB composition of those stretched subs - SHO style:

Do little hue tweaks here to adjust palette - either hue shift or channel mixer which ever you prefer

Hue shift to "equalize" background (in fact it made it more blue and less red)

or Channel mixer:

Now, once you found color combination that looks best to you, it's time to do luminance transfer. There are many options available, but let's go with basic one - copy ha stretched lum channel and paste it as another layer on top of this color image.

Set layer mode to luminance (Gimp offers three different kinds LCH and HSV - lch has luminosity and lightness, while HSV has value) and voila, you have your composition with Ha as luminance:

Now you can go and reduce color noise and do other processing touch-ups as you please.

[vlaiv]

And something we could call "final" version - courtesy of StarNet++ (stars removed from color composition and then re added as white stars from Ha channel - no magenta issues no more 😞

[Ryan_86]

That's amazing Vlaiv condsodering how little data I have. Did you use just sub 8, 9 & 10 of the Ha. I will attempt using your workflow👍🏼

Much appreciated pal. 

Ryan

[vlaiv]

13 minutes ago, Ryan_86 said:

That's amazing Vlaiv condsodering how little data I have. Did you use just sub 8, 9 & 10 of the Ha. I will attempt using your workflow👍🏼

Much appreciated pal. 

Ryan

No, I stacked all 10 of them. I did use outlier rejection (that is sort of hot pixel correction) to prepare subs. I then used "split bin" - it's a sort of binning technique where you split your subs into larger number of subs without actually binning them and then stack all of those - which is very much like first binning then stacking but has some advantages - like dealing with remaining hot pixels and not introducing pixel blur. I did bin x3 in this fashion - that is why resulting image is x3 less in height and width than original data (there will be no difference when viewed at screen size - like here in forum post, but you will see difference if you zoom to 100%). I opted to bin because for this data - SNR has priority over detail captured (and let's face it - stars are not quite round to be viewed at full resolution).

In the end I used special stacking method that I developed that accounts for different SNR of individual subs - a bit like PixInsight weighted average, but mine does not assign weight to whole frame but bunch of weights to groups of pixels and noise estimator is different. I used that approach because of different temperature between Ha subs.

For other channels I just used sigma reject stacking - they are pretty uniform in SNR.

Last step was to remove background - again I used my algorithm for that - it's pretty straight forward - you start by iteratively selecting lowest value pixels in the image (like sigma reject - but instead of rejecting you actually look at those pixels as background) and fitting plane thru those "background" pixels only - that background is subtracted and process is repeated (some pixels that were too bright because they were part of gradient are now in background and we need to examine them as well) iteratively until residual gradient is rather small (less than 0.000001 or something like that).

You have resulting stacked and wiped linear data attached as fits above - so you can download those and have a go at processing that as well.

Do have a look at StarNet++. Last image was done with it. Here it is similar workflow except I did following:

- Ha luminance stretched layer was processed in StarNet++ to get starless version. Stars were extracted as regular layer + starless layer set to difference (or subtract or whatever operation is for subtraction) - that leaves only stars.

- Color layers were processed in StarNet++ and then combined. After combination I did channel mixer to get right "tone" to the image - much easier since you don't have any stars and you don't have to worry about odd magenta colors. Raise level of green in red channel to get that golden tone and remove green cast (converts green to yellow), and subtract a bit of blue channel from red to get better blue tones. Raise a bit of green in blue channel to get that "sky like" blue rather than deeper sort of marine blue.

- Apply starless Ha luminance to resulting color composition as described above

- add stars as top player with screen blend mode (I think it was screen - one that only lets light parts - stars from top layer).

 

[Ryan_86]

Hi Vlav,

I managed to have a good go at salvaging what data I had. Being my first CCD/Narrowband image I am really happy with my attempt. Also I am excited to see what data I can capture with consistent cooling and more calibration frames.

Its far from perfect but a good start for myself I feel.

Thanks again for all your help pal. Stargazerslounge is a total god send for people like myself

All the best

Ryan 

Edited December 29, 2019 by Ryan_86

[carastro]

To be honest, your camera is probably holding you back if it is known to be a noisy camera.  Is there anything you can do about replacing it in the near future?

Carole 

[Ryan_86]

Hi Carol, 

I haven't long bought the camera to be honest. SX are offering a modification to the main board to decrease thr readout noise (typically between 20 to 30%). I will give it a try along with dark frames, and ensuring the camera is consistently cooled 😬

If all else fails then I will be looking at alternative options 👍🏼

Ryan