M37
M37 - Click here for full resolution
Messier 37, also known as NGC 2099, is the brightest and richest open star cluster in the constellation Auriga, located approximately 4,500 light-years from Earth. It was discovered by Giovanni Battista Hodierna in the 17th century and independently cataloged by Charles Messier in 1764. M37 contains over 500 stars, with an estimated age of about 350 million years, making it a relatively young cluster. It has an apparent magnitude of 5.6, making it visible to the naked eye under dark skies and an excellent target for small telescopes or binoculars. The cluster spans about 25 light-years across and features a dense core surrounded by a more diffuse halo of stars. It includes several prominent red giant stars, which stand out with their reddish hue against the cluster's many blue-white main-sequence stars. M37 is also rich in metallicity, indicating that its stars formed from material enriched by earlier generations of stellar evolution.
source: ChatGPT
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NGC2099
n.a.
Globular Cluster
Auriga
05h 52m 18s
+32° 33.2′
4.400 ly
5.6
05 January
85º S
Conditions
M37 is best visible during Winter. Maximum altitude reached is 82° in early January. M37 as a stars-only object is a practical ‘full moon’ target that is not too much effected by the light of the moon. M37 was photographed over 5 nights during mid-December and mid-January when the moon was >75% illuminated. Imaging took place from the remote observatory at IC Astronomy in Oria, Spain.
Equipment
The default rig at the observatory was used. The core of this rig is a Planewave CDK-14 telescope on a 10Micron GM2000 mount, coupled to a Moravian C3-61000 Pro full-frame camera. The RoboTarget module in Voyager Advanced automated the process to find optimal time-slots during astronomical night.
Telescope
Mount
Camera
Filters
Guiding
Accessoires
Software
Planewave CDK14, Optec Gemini Rotating focuser
10Micron GM2000HPS, custom pier
Moravian C3-61000 Pro, cooled to -10 ºC
Chroma 2” Luminance, Red, Green and Blue unmounted, Moravian filterwheel L, 7-position
Unguided
Compulab Tensor I-22, Windows 11, Dragonfly, Pegasus Ultimate Powerbox v2
Voyager Advanced, Viking, Mountwizzard4, Astroplanner, PixInsight 1.9.2
Imaging
M37 is a typical broadband object, that is not very critical to conditions of moon interference and were shot when moon illumination was >75%. To minimise moon the effect of the moon light all images, also the R,G and B images, were shot as 3 min exposures. The total exposure was 10.9h.
Resolution (original)
Focal length
Pixel size
Resolution
Field of View (original)
Rotation
Image center
9492 × 6276 px (59.6 MP)
2585 mm @ f/7.3
3.8 µm
0.30 arcsec/px
47' x 31'
179.5°
RA: 05h 52m 18.029s
Dec: +32° 32’ 47.37”
Processing
All images were calibrated using Darks (50), Flats (50) and Flat-Darks (50), registered and integrated using the WeightedBatchPreProcessing (WBPP) in PixInsight. All further processing was done in PixInsight, including the use of scripts and tools developed by RC-Astro, SetiAstro, GraXpert, and others. For a step-by-step description of the processing techniques applied, see process flow below.
As an initial attempt, FBPP was used to calibrate the images instead of WBPP. Unfortunately the resulting integrated files were not great. There was a weird gradient that appeared hard to remove, and the rejection algorithm had been rejecting pixels in such a way that artefacts remained visible in the final output. When WBPP was run, the output was much much better. It rejected 10 bad frames, the rejection maps looked much more even and the local normalisation resulted in a much more natural gradient that was easier to remove. FBPP can work well on a good dataset, but in my experience WBPP remains the more consistent and reliable tool.
For luminance MultiscaleGradientCorrection (MGC) was used to remove the gradient. And while it took a view iterations to find the right parameters, the result was slightly better than the GraXpert output. For the RGB image it was the other way around. The MGC seemed to introduce some gradients around the center of the cluster and in a ring around it. Gradient scale, structure separation and smoothness were all modified to improve the results, but it never really got there. GraXpert on the other hand removed the gradient quickly and effectively. Perhaps applying MGC to the individual colour channels rather than the RGB image, might have given better results. But that is a lot more work with FluxCalibration etc.
Stretching a stars only image can be a bit tricky. The various scripts and pixelmath formulas usually wash out colour quickly. To maintain colour, Arcsinh stretch is much more preferred, but will always have to be followed by a second stretching method. GHS can turn stars into strange looking objects with super bright tiny cores on a kind of a wide halo-like background. This time I did use the GHS tool, but used the Midtone Transfer method. This is essentially the same as HistogramTransformation. To focus on the colour, Colour-mode was used instead of RGB. Two consecutive stretches, the first with 100% blend and the second with a 50% blend, did the job. Although not automatic as with some of the scripts, this worked pretty well for a stars only image like M37.
On a star cluster like this, it is worthwhile paying some extra attention to the Luminance, for it not to overpower the RGB image too much, or colours would wash out quickly. This means a careful stretching to begin with. But this time I also added some star size reduction. Mike Cranfield has developed a script for that, called StarReduction. It requires a separate starless image, which was easily created using SXT. There are several Star reduction methods, of which several were compared. I ended up with the Transfer Method as being the one giving the best results. A stretch factor of 0.3 was used. The RGB image by the nature of its colour-focused stretching did not need any star size reduction.
Remaining processing was done in a fairly standard manner.
Processing workflow (click to enlarge)
This image has been published on Astrobin
