Ok.
Thanks to all who has helped with this.
Turning off Optimization (scaling) in the calibration (both BPP script and manual) fixed the problem with 'Warning: No correlation...' issue. One down.
Now I need the fine tune the calibration parameters (integration of darks and flats).
What I would need is some help with interpreting the results from the Integration console.
My own visual subjective appreciation of the result tells me that the integrated picture I get by using iTelescopes calibrated frames LOOK better than when using my own calibrated frames.
BUT if I understand the output of the integration script there is more noise in the image made by iTelescopes frames.
Ie. the picture LOOKS better to me but it is actually worse.
I am the first to admit that I have a very limited experience in visually inspecting an astronomical image and it might be that my lifelong experience in handling "normal" pictures is fooling me.
OR it might be that I do not understand the readout from the console.
Image integrated with frames calibrated by BPP
Output from Noise evaluation script
?K = 7.157e-005, N = 4276627 (67.98%), J = 4
Output from integration script
Integration of 17 images:
Pixel combination ......... average
Output normalization ...... additive + scaling
Weighting mode ............ noise evaluation
Scale estimator ........... iterative k-sigma / BWMV
Range rejection ........... range_low=0.000000 range_high=0.980000
Pixel rejection ........... Winsorized sigma clipping
Rejection normalization ... scale + zero offset
Rejection clippings ....... low=yes high=yes
Rejection parameters ...... sigma_low=4.000 sigma_high=2.000
MRS noise evaluation: done
Computing noise scaling factors: done
Gaussian noise estimates : 7.1574e-005
Scale estimates : 1.1722e-004
Location estimates : 1.2052e-003
SNR estimates : 5.5517e+003
Reference noise reduction : 1.5111
Median noise reduction : 1.6573
Image integrated with frames calibrated by iTelescopes system
Output from Noise evaluation script
?K = 8.347e-005, N = 4712765 (74.91%), J = 4
Integration of 17 images:
Pixel combination ......... average
Output normalization ...... additive + scaling
Weighting mode ............ noise evaluation
Scale estimator ........... iterative k-sigma / BWMV
Range rejection ........... range_low=0.000000 range_high=0.980000
Pixel rejection ........... Winsorized sigma clipping
Rejection normalization ... scale + zero offset
Rejection clippings ....... low=yes high=yes
Rejection parameters ...... sigma_low=4.000 sigma_high=2.000
MRS noise evaluation: done
Computing noise scaling factors: done
Gaussian noise estimates : 8.3471e-005
Scale estimates : 1.0707e-004
Location estimates : 1.5804e-003
SNR estimates : 3.4925e+003
Reference noise reduction : 1.2206
Median noise reduction : 1.2180
The one that LOOKS worse to me (calibrated by BPP) has an SNR of 5.5517e+003 and the one that looks better has an SNR of 3.4925e+003
Should I not strive for a higher SNR??
Also: How should I read the output from the noise evaluation
?K = 7.157e-005, N = 4276627 (67.98%), J = 4
Have tried to search the forum for an explanation what the output means but so far no luck.
There is a lot of questions here but I am really struggling to LEARN what I am doing. Have used PS for +15 years and the only thing I learned there is workflows. Do this to achieve that. I never understood why something worked.
PI is very different and I appreciate that a lot.
Attaching Dropbox links to both images.
https://www.dropbox.com/s/bgildmbfcacs4yz/own_calib.fithttps://www.dropbox.com/s/micnpyeaxt8q7v7/iTelescope_calib.fitRegards
Mats