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MartinB

Mure denoise and cmos camera - help needed!

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PI has an uncanny capacity to make me feel really stupid!  I hear that Mure Denoise is a very good tool to be applied as a first processing procedure to an integrated image.  As usual I have to set some correct parameters in the boxes and that is the challenge.  I would be very grateful for help with what looks like a great tool.

I have a ZWO ASI 1600mm pro camera and have a calbibrated, aligned and combined image from 50 lights in Ha.  

I put 2 darks (300secs matching my exposure times) into the DarkBiasNoise estimator and this came up with an offset of 800.00 DN and Temporal noise 40.48 DN

moving on to the Mure Denoise script the combination count is easy - 50 (or is that too easy!), interpolation method I'm guessing at Lanczos-3 (I used auto and didn't know to check at the time).

Now for the gain.  I was using a gain setting of 150 which corresponds with an actual gain value of 0.9 e-/ADU but the unit in PI is e-/DN (I know DN is a unit of force but don't know whether that corresponds with e-/ADU)

Gaussian noise - from the noise estimator tool I have a value for "temporal noise" of 40.48 DN.  I don't know if this is the figure I should enter under gaussian noise but this is what I have entered

Offset - the noise estimator gives a value of 800 so this is what I have entered

Variance scale - I am leaving this at 1 since I didn't create a log of the integration.  The subs were very consistent so should be ok.

Cycle spin count - left at the default of 8

At some point a gaussian noise value of 1.3 got entered as a value but I'm not sure how this happened!

After running the script I get an image of the noise and my light image has an undo arrow showing that the process has been applied.  However, when I undo and redo the image doesn't change even when highly zoomed.  There is noise clearly visible but it hasn't been affected by the process.

I am sure I am making some very basic mistakes and would be grateful for guidance!

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AfaIk, DN and ADU are the same, a digital unit. Otherwise, I can't help, I've never come to grips with Mure denoise. 

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Thank you Wim, that is actually very helpful.  So DN (in this context) simply means digital number and corresponds with ADU.  Still not there with this but I have found a set of numbers to imput which seems to very effectively reduce the background noise whilst leaving signal intact and free of artefacts.  More study needed to fine tune but I am now refining the questions I need to ask!

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28 minutes ago, MartinB said:

Thank you Wim, that is actually very helpful.  So DN (in this context) simply means digital number and corresponds with ADU.  Still not there with this but I have found a set of numbers to imput which seems to very effectively reduce the background noise whilst leaving signal intact and free of artefacts.  More study needed to fine tune but I am now refining the questions I need to ask!

What numbers did you land on? There is a tutorial on the ip4ap website which explains the usage of the tool, but when I followed the instructions I got the same resul as you; namely a nice noise image but the integrated file looked identical...

If you run image integration prior to loading the MureDenoise script you can then hit the 'load variance scale' which populates the values for combination count and variance scale.

I think offset should be 0; your integrated stack will be fully calibrated? Conversely the dark bias noise estimator script comes up with an offset because you feed it 2x uncalibrated darks?

 

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Thanks JimJam.  Yes, I fianlly worked out that the offset needed to be zero, more by trial and error than anything but I understand now.  I gather that you can get a good idea of detector gaussian noise by dividing read noise by detector gain (based on the ZWO graph for the camera).  This gives me a value of 1.9 however this only produced a very minor effect.  FlatSNRestimator reported a gain value of 0.054  which doesn't seem to make sense.  I'll have to double check but I'm pretty sure I was using an original flat with this tool rather than one which was dark calibrated.  The calculated detector gaussian noise figure from this value was 3.15.  This appears to have worked a like a charm.  The background is nicely smoothed with no impact on faint stars or faint wisps of nebulosity.  I can see nothing untoward going on in the background.  So I don't understand the values but I do understand the evidence of my eyes!

I really appreciate your help JimJam, thank you

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I wonder if this could actually be a difference between DN and ADU because the ASI1600 has a 12bit ADC:

https://www.cloudynights.com/topic/573886-sub-exposure-tables-for-asi-1600-and-maybe-qhy163/?p=8068575

I was testing on a ha sub captured at gain 200, so 0.48 e/ADU. When I entered this I got the same result as you; no change. Decreasing this to 0.03 as measured by flatsnresttimator and I am starting to see results.

I then tested the gaussian noise value. A small value (measured/10) got minimal/no change. A big value (measured * 5) got a weirdly over-smoothed result.

 

Edited by jimjam11

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7 hours ago, jimjam11 said:

I wonder if this could actually be a difference between DN and ADU because the ASI1600 has a 12bit ADC:

https://www.cloudynights.com/topic/573886-sub-exposure-tables-for-asi-1600-and-maybe-qhy163/?p=8068575

I was testing on a ha sub captured at gain 200, so 0.48 e/ADU. When I entered this I got the same result as you; no change. Decreasing this to 0.03 as measured by flatsnresttimator and I am starting to see results.

I then tested the gaussian noise value. A small value (measured/10) got minimal/no change. A big value (measured * 5) got a weirdly over-smoothed result.

 

That actually makes sense, since with a 12 bit ADC (zwo cameras) the 12 bit output is stored in the high end of a 16 bit word; 1 ADU = 16 DN. (16 = 2^4 where 4 =16 - 12.) 

0.48 e/ADU = 0.48/16 e/DN = 0.03 e/DN

Good thing I wrote "afaIk" before, because I didn't then, but now I know farther. Always nice to learn new stuff. :)

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You two are my friends for life!

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