M1 - Crab Nebula
The Crab Nebula is a supernova remnant and pulsar wind nebula in the constellation of Taurus. The common name comes from William Parsons, 3rd Earl of Rosse, who observed the object in 1842 using a 36-inch (91 cm) telescope and produced a drawing that looked somewhat like a crab. The nebula was discovered by English astronomer John Bevis in 1731, and it corresponds with a bright supernova recorded by Chinese astronomers in 1054. The nebula was the first astronomical object identified that corresponds with a historical supernova explosion. At the center of the nebula lies the Crab Pulsar, a neutron star 28–30 kilometres across with a spin rate of 30.2 times per second, which emits pulses of gamma and radio waves
source: Wikipedia
NGC1952
Sh2-244
Supernova remnant
Taurus
05h 35m 52.08s
+22º 01’ 55.6”
07 January
59º S
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Conditions
M1 is a typical winter object with peak visibility around December, January. Images were taken on four nights, between 12 December and 17 December 2022 from the backyard in Groningen, The Netherlands (53.18, 6.54). Best time to observe this target is between November and February. Most of the images were taken at altitudes between 30 and 60 degrees.
Equipment
M1 is a relatively small target and the combination of the Takahashi TOA-130 with the ZWO ASI533MM Pro gives a large enough field of view to capture the whole target and quite a bit of its surroundings. It can be photographed in many different color palettes, but the choice here was made for a traditional Hubble palette, with H-alpha, OIII and SII narrowband filters. No separate RGB images were taken for star colours.
Telescope
Mount
Camera
Filters
Guiding
Accessoires
Software
Takahashi TOA-130, Sesto Senso 2
10Micron GM1000HPS, EuroEMC S130 pier
ZWO ASI533MM Pro, cooled to -15 ºC
Astrodon 1.25” SHO (5nm) mounted, ZWO EFW 8-position
Unguided
Fitlet2, Linux Mint 20.04, Pegasus Ultimate Powerbox v2, Flip Flat, MBox
KStars/Ekos 3.6.2, INDI Library 1.9.9, Mountwizzard4 2.2.8, PixInsight 1.8.9-1
Imaging
Imaging M1 was done in the second half of each night, with the first half of the night reserved for another target. The narrowband images were shot using 5nm filters. The usual capture conditions for this setup is 300s at gain 100. It was a week of freezing temperatures and unpredictable weather forecasts. Generally high humidity, sometimes fog and often clouds rolling in. Many subs were lost due to these suboptimal conditions.
Images were recorded during 4 frosty evenings in December 2022. Moon and high humidity were challenges. With moon and occasional clouds rolling through, sky was not very dark, SQM around mid 18.
Geometry
At 9MP the final image does not have super high resolution, but the details in the Crab Nebula still come out quite well. The 0.8 arcsec/px pixel scale helps with that as well. The image is almost pointing North, with only a small 13 degree turn counterclockwise.
3008 ×3008 px (9.0 MP)
1000 mm @ f/7.7
3.76 µm
0.774 arcsec/px
0º 38.8' x 0º 38.8’
-13 degrees
RA: 05º 34’ 32.000”
Dec: +22º 00’ 50.60”
Resolution
Focal length
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Resolution
Field of View
Rotation
Image cente
Processing
All frames were calibrated with Dark (50), Flat (25) and Dark-Flat frames and registered using the WeightedBatchPreprocessing script. Image frames were then normalized and scaled using the NormalizeScaleGradient script and integrated using NSG parameters. The image was built up using two separate processing paths, one focused on the object, the other on the stars.
The main image was created using the Hubble-palette, mapping SII to the Red, H-alpha to the Green and OIII to the blue channel. The resulting image was very blue in a linked stretch. Using the PixelMath SHO balancing script developed by Bill Blanshan did a very good job in bringing out the typical colours in the object, while having limited magenta artefacts. Then the object was sharpened using a new deconvolution tool, called BlurXTerminator. This was the first image where I applied this very exciting new tool. It turned out that the default settings were far over sharpening the object, creating a very unnatural look. In order to get the desired result, I turned off the Automatic PSF function and played with both PSF diameter and sharpening settings, while having a real time preview of a small part of the image open. I don’t think there is a place where you can read what the process uses for Automatic PSF. Probably 2.5 pixels is a bit lower though than then Automatic PSF. It seemed to give a bit more ‘natural’ look, but since it works in conjunction with the sharpening slider, it is difficult to tell for sure. Sharpening default is at 0.9, which was way too high for my taste. At 0.5, and with the PSF (probably?) a bit lower than automatic, the result was impressive while maintaining a very natural look. Since stars were to be added separately, not much attention was payed to the settings there.
The effect of BlurXTerminator with before (left) and after (right) comparison.
Then it was time to stretch the image, using a combination of a mild HistogramTransformation, followed by a Hyperbolic stretch to increase contrast in the nebulous regions. There was a tiny magenta color cast in the background which was removed using Backgroundneutralisation. However, when that was applied, there was a hint of green in it, which was reduced using SCNR while masking off the nebulous area. The noise was removed using NoiseXTerminator. Also this AI-based tool can easily overdo the effects, so modest settings were used of 0.5 for denoise and 0.25 for detail. After these steps, the colour and detail of the nebula were actually pretty good. Still the stars were removed (StarXTerminator), to have them replaced using more natural colours. The starless image was a great opportunity to work on the background a bit more, mainly to bring it to a level of 0.1, which is typically a very natural looking dark background.
Stars in an SHO palette never really have great colours. Often the reds are a bit magenta looking and also the blue does not come out very well. The best solution is to shoot a separate small set of RGB images, purely for the stars. An alternative is to create an HOO image for the stars. The H-alpha signal is a true red signal, making it a good representative for red stars. The two OIII wavelengths of 496 and 500 nm are of a blue-green (teal) colour, so a good representative of blue stars.
So an HOO-palette was assembled and was balanced using the Bill Blanshan PixelMath script. Then the image was modestly stretched first using ArcsinhStretch to preserve as much colour as possible. Then the final stretch was done using GHS. The stars were extracted using StarXTerminator and brightened up just a touch using CurvesTransformation. As an experiment color calibration using PCC was applied, but this had hardly any noticeable effect. Overall using this technique definitely resulted in better star colours than is typical in SHO images, although the colours remain a bit muted when compared to true RGB images.
Finally the stars from the HOO palette were placed back into the SHO image using PixelMath, which completed the final image.
Processing workflow (click to enlarge)
This image has been published on Astrobin.
