NGC2237 - Rosette Nebula
NGC2237 - Rosette Nebula. Click here for full resolution image.
The Rosette Nebula is an H II region located near one end of a giant molecular cloud in the constellation of Monoceros, about 5,000 lightyears from Earth. It is number 49 in the Caldwell catalogue. The nebula has multiple NGC codes, all representing slightly different areas of the nebula. Typically NGC2237 is used to indicate the whole nebula.
In the middle of the nebula is an open cluster of very bright and extremely hot stars. This cluster is referred to as NGC2244. UV radiation from these stars is heating up the surrounding gas areas to a temperature of 6 million K. Stellar winds from the star cluster have created the hole seen in the middle of the nebula. The pressure from these winds on the interstellar matter causes star formation.
Planning
Object
Visual Magnitude: 5.5
Apparent size: 80 x 60 arcmin
R.A.: 06h 31m 22.53s
Dec: +05º 02’ 05.6”
Conditions
Astr. night: 19:38
Astr. Dawn: 05:55
Moon: 67%
Moon set: 4:17
Humidity: 81-84%
Pressure: 1028-1036 hPa
The Rosette Nebula is a typical winter object, with peak altitudes around January through March. Images were taken at sessions on February 14 and 15, 2019. The moon was very bright during these days, but narrow band imaging typically is not much affected by a bright moon. The object was getting low to the horizon in the second half of the night, and several frames were lost due to the object been obstructed by trees.
Capturing
The Rosetta Nebula is a very strong emitter in the H-alpha line. So great photos can be made mapping the H-alpha data to the red channel, bringing out a very rich red nebulous structure. Another approach often seen is using the Hubble palette. In this palette data is collected in the H-alpha, SII and OIII lines and mapped to the Green, Red and Blue channels respectively. The latter approach was used here.
It is a very large nebula, with an apparent size of 80 x 60 mm and is a perfect target for a wide-field telescope. In February 2019 the FSQ-106 was added to the observatory and this was the first target that was imaged with it. The FSQ-106 is f/5.0, compared to f/7.7 for the TOA-130, so a lot faster. This was directly noticeable in the exposures. With the TOA-130 typical narrow band exposures are in the 180-300s range, with Gain 300. In the case of the FSQ-106, this could easily be reduced to 180s at gain 139 (unity gain).
The images were taken on two consecutive days, giving the luxury of not having to setup the system twice. General conditions were good, with reasonably good seeing, relatively cold at -7ºC and no wind.
Technical details
Telescope
Mount
Camera
Sensor Temp.
Takahashi FSQ-106
10Micron GM1000HPS
ZWO ASI1600MM Pro
-25ºC
Exposures
Ha (5nm)
OIII (5nm)
SII (5nm)
Total Exposure:
40 x 180s @ Gain 139/21
40 x 180s @ Gain 139/21
40 x 180s @ Gain 139/21
6h
Processing
All frames were calibrated with Bias (100), Dark (50) and Flat (25) frames, registered and stacked using the BatchPreprocessing script. The first impression of the integrated images for each colour channel was that they all showed a very nice amount of detail and sharpness into the far corners. These seemed like satisfying results from the new telescope. It appeared that using the same exposure settings for each of the colour channels led to largely different signal strengths. The H-alpha channel had a mean signal of 445 ADU, the OIII channel was significantly higher at 736 ADU and the SII channel significantly lower at 331 ADU. Signal strengths were brought in line with each other by applying a Linear Fit of the OIII and SII channel with the H-alpha as the reference. With this balanced input level, the SHO image could be made using PixelMath applying equal weight to each channel. SII is mapped to Red, H-alpha to Green and OIII to Blue.
A small magenta cast was eliminated using DynamicBackgroundExtraction and background noise was reduced by applying MultiscaleLinearTransform to scale 1 (3,1,2) and scale 2 (2,0.5,2). Then it was time to stretch the image into its non-linear state.
In most SHO images, stars will have a magenta halo around them. There are different ways to remove that. In this case the method using SCNR was used. First, the image was inverted. Inverted magenta turns green. Green is then removed using SCNR and the image is inverted back into its normal colours. The following images show the effects of each step.
The next step is to create and enhance the typical colours that the Hubble palette is known for. As a first time applying this technique, there was a bit of trial and error to get the colours right. But ‘right’ is a very subjective term. This is really all about finding something aesthetically pleasing, that fits your taste and conveys a desired atmosphere. This is definitely art, not science. With that caveat out of the way, the steps were roughly as follows.
The image manipulation largely hinged on specific colour masks, to selectively affect specific areas of the image. Those masks were easily prepared by the script ‘ColorMask’, that can be found under Scripts>Utilities. The generated masks were Cyan, Green, Magenta and Yellow, with Mask blur set to 3. Using CurvesTransformation, the adjustments were made. For a very good demonstration of how you can apply masks and their effects, you may want to check out the video by Christopher Gomez that you can find here. For NGC2237, the various steps were applied as follows
Green mask: decrease green, increase red and contrast enhance RGB/K (creates the typical green/brown colours)
Cyan mask: decrease green and red, increase blue and RGB (enhances the blues)
Magenta mask: contrast enhance RGB/K (reduces any remaining magenta-hue and intensifies the blues)
Cyan mask: contrast enhance RGB/K (intensifies blues)
Yellow mask: increase red, RGB/K and saturation (highlights the golden colours)
Again, this is all a matter of taste, and once it was understood better how the masks behave (straight or inverted), it was very inviting to keep tweaking to bring out the desired colour palette. It was also found useful to have a look at examples of how other people have processed the same object. It helps developing a sense of what you like and don’t like in these Hubble palette images.
The CurvesTransformation tool is very sensitive, so very small adjustments will have a significant effect. In most cases just the mid-points of a certain colour channel were increased or decreased, which creates a natural effect of enhancing or fading a certain colour. In the case of contrast enhance, an S-curve was applied, pulling down the lower brightness levels and pulling up the higher brightness levels.
The heavy lifting was now done on the image. Next steps included some additional noise reduction and enhancing of dark structures. Star-size was reduced using MorphologicalTransformation (Amount 0.5, Size 9) under a star mask. After inverting that mask, the structures in the image sharpened up quite nicely with Unsharpmask (Stdev 2, amount 0.8). In final touches the brightness and contrast were enhanced using a combination of HistogramTransformation and CurvesTransformation.
This image has been published on Astrobin.
