NoiseEvaluation and Subframeselector's "noiseOfImage"

[ChoJin]

Hello,

following
http://pixinsight.com/forum/index.php?topic=5764.msg39382#msg39382
and
http://pixinsight.com/forum/index.php?topic=8434
I'm trying to make sense of the noise evaluation functions (in both the standalone script and within the subframeselector)

obviously I have a few questions:
- why both scripts are not using BWMV() to scale the result and therefore improve the robustness to be able to compare properly the noises between frames/subframes?
- in subframeselector's noiseOfImage function I can see it is computing the value for layer4 first and going down to layer2 until it find a suitable value. Why?  I don't understand why we don't take the overall RMS or at least the layer1?

- and a side question: with the current noise evaluation in the subframeselector, if I'm using it, does it mean i'm giving up the improved scaled estimators from within the ImageIntegration Process? Should I therefore just use it to reject some frame and rely on the ImageIntegration Process for the weighting?

Sorry, I'm new to PixInsight, hence my questions might be very trivial for most of you

[mschuster]

The code you see supplied by Pteam, to match II algorithm. The iteration across layers provides robustness. The script uses a scale estimator used as the only option in prior II. Eventually I will update and provide the newer options.

Thanks,
Mike

[ChoJin]

Could you explain further the layer robustness?

I always read that most of the noise is from layer1&2. Wouldn't it be less accurate to compute the noise value from layer4? Or maybe the idea is that it doesn't really matter as long as you can compare the values between the subframes?

[mschuster]

II documentation has a reference for the algorithm. PTeam may be able to supply additional information.