The year started out pretty bad – a single night of observations on January 13, 2022. I put the ASKAR 135mm f/4.5 APo to work, paired with a ZWO ASI 533 MC. A couple of targets for the night, M35, M44, M51, M87, M95, and NGC4565.
Messier 35 is an open cluster in Gemini with approx. 400 stars contained in a sphere of 11 light-years diameter. The image is made up from 30 individual photos with 70s exposure time each – a total of just 35 Minutes. The conditions were less than optimal with a Moon only five days from its 100%. The cluster itself is located at the upper edge of the image to allow for other objects to appear in the overview, namely IC443 and the NGC2174/NGC2175 complexes.
Next target up was Messier 44, also known as “Praesepe” or “Beehieve Cluster”, an open cluster located in the heart of the Cancer. It is a relatively easy target, given some acceptable dark skies and preferably some binoculars. This target requires a wide field of view although we will later see that a “close-up” is also gorgeous.
Speaking of “gorgeous” – the annotated version, of course, has its value but this one comes out a bit nicer when adding some star spikes and color.
Next up was Messier 51 – the famous “Whirlpool Galaxy” in Canes Venatici. The galaxy is some 23 light-years from Earth and I decided to take the photo covering the area between M51 in the upper-right corner and NGC5297, a spiral galaxy in 110 million light-years distance, in the lower-left corner.
A bit to the south of Canes Venatici are the three constellations Coma Berenices, Virgo, and Leo. They are holding large numbers of galaxies. The first wide-field is targeting Messier 95, a barred spiral galaxy some 33 million light-years away in Leo. It forms a group of two together with Messier 96 and a bit off is Messier 105 with NGC3384 and NGC3389.
Finally, the last image of that night went to NGC4565 in Coma Berenices, the well-known “Needle Galaxy”. The beautiful spiral galaxy that we are looking at “edge-on” is approx. 57 million light-years away. Again, it will be revisited later with the larger telescope.
That last photo concluded the January observation night – it was supposed to remain the only night that month and only at the end of February, it would clear up again.
Right after finishing up “my” shooting of M31 – the “Andromeda Galaxy” – with my Skywatcher 72ED and my Nikon D7500, I switched to a dedicated astro camera, a ZWO ASI 533 MC Pro. It has two big advantages over the standard DSLR:
It can be actively cooled so I can always take my images with the same chip temperature (and re-use my darkframes)
It does not have IR Cut Filters and therefore accepts light in wavelengths the unmodified Nikon D7500 cannot
The initial integration of the images (80 x 70s, 21 x 180s for a total of 2:36h) shows a nice result. And zooming in shows the superiority of a camera sensor cooled down to -10°C (plus I used darkframes this time): almost zero background noise!
The rest is the same basic processing workflow that I have done with the Nikon images: Color Calibration, Stretching, some Curve Transformation…done.
A direct comparison of both images – the one from the Nikon on the left, the one from the ZWO ASI 533 on the right – shows: they both work well, the Nikon’s image is an accumulated 12+ hours, the ZWO ASI 533 is an accumulated 2+ hours of exposure time.
The overall image also shows: the sensor of the ZWO ASI 533 is smaller but the items appear larger when compared to the Nikon. Photographing all of Andromeda probably requires a Mosaic of 2×1 or 2×2 frames, depending on what should be achieved.
Just out of curiosity (and stepping ahead a few month) I am also showing a comparison with a monochrome camera, a ZWO ASI 1600 MM with a Luminance filter:
Mono Cameras are a whole different thing – and I will talk about them later. But for now, let’s conclude: taking Deepsky Images with a DSLR is (for broadband targets such as galaxies) completely fine! The advantage of a dedicated color astro camera is mostly the ability to cool the sensor (and reduce the background noise reliably and reproducible) and the lack of the IR (Infrared-cut) filter on the One-Shot Color Camera (OSC).
Much more important are a good and steady mount that allows for pinpointed stars when guiding for say anywhere from 70s to 180s and a good telescope (preferable with a motor focus but more on that also later).
Suggestion from my side: put your money in the mount first! Then upgrade the optics and finally the camera. Pick your targets wisely and match them to your equipment. And don’t save money on the processing side! Like in many other cases: buy wisely! Those that buy “cheap” will either give up or buy twice…
By September 2020, and after the initial positive results with astrophotography from my backyard, I had invested into some “upgrades”. Initially, I was out just with the tripod and the Nikon D90 and several of my Nikon lenses.
Next thing that happened: the Nikon D90 got replaced by a Nikon D7500 and shortly afterwards, the tripod was equipped with an Omegon LX2 mechanical star tracker. Which did not last long (I mean, it did its job but had limitations) – it was replaced with a Skywatcher HEQ5 Pro Mount and the Nikon lenses made room for a Skywatcher 72ED telescope, together with a Skywatcher 50ED Guide Scope and a ZWO ASI 120 MM Guiding Camera. Also, a switch was made from a simple intervalometer, controlling the Nikon exposures to using dedicated astrophotography software. The Nikon D7500 remained in place for some last set of photos of M31, the “Andromeda Galaxy”.
Images were taken during several sessions between September 2020 and November 2020 – a total of 12:28 hours of exposure time.
This time, some darkframes “survived” the times so I decided to apply them globally, although they did not match the temperatures of each image session – remember, the Nikon D7500 is a regular DSLR so darkframes should match the temperature the light were taken at.
Pre-processing a large number of images, including the creation of three master darkframes, takes a little while – my computer was busy for some 26 minutes. Like before, the next step is to debayer the images and then do the star alignment – this time, I had sorted out the “bad images” so I spare you that step.
With an Deepsky Object (DSO) that large, the background extraction needs to be performed more selectively using the DynamicBackgroundExtraction process which allows the user to select what is “background” and what not.
Next are then the BackgroundNeutralization and the PhotometricColorCalibration processes – once done, the colors have been adjusted more to their natural look.
The large number of source images has already made sure that the background noise is very low but running a bit of noise reduction makes it even better. Now, we are ready to stretch the image finally.
What comes now – again – is a matter of “taste”. But one thing I want to show you is how to work with the “galaxy” and preserve the stars around it in their current state (or handle them individually).
There is a PixInsight (and also PhotoShop) process written by Russel Crowman (see his Website) which allows PixInsight to “separate” the stars from the background. If you tell the process to also generate a Star Image, you can work both on the background and on the stars separately.
This now provides almost endless possibilities – the sample below shows in the upper left corner an image of the background that was HDR-tunes in Photoshop, the regular image center bottom and the star-mask (intensified in Photoshop).
Whatever we do to the individual images – we can use PixelMath to combine them afterwards:
So for the moment, this is the result in PixInsight that comes from the long hours of photographing M31 in 2020
This was the last image that I produced using the Nikon D7500 DSLR – afterwards, I switched over to a dedicated AstroCamera, a ZWO ASI 533 MC – but that is a different story…
With the success of the “Leo Triplet” and with the Nikon D90 replaced with a Nikon D7500, I decided to take another “go” at the big galaxies in Ursa Major, M81 and M82.
This was also my first “multi-session” attempt, with the images being shot over several nights (and with slightly different focal lengths).
May 25, 2020: 37 images of 45s each with the lens settled at 250 mm, f/5.6
May 28, 2020: 42 images of 45s each with the lens settled at 300 mm, f/5.6
May 28, 2020: 12 images of 60s each with the lens settled at 300 mm, f/5.6
That gives a total of 91 images with a total of 71 minutes. One of the first questions people often ask is: “Can you combine images from multiple nights?” and the second one, a bit more complex, is “Can you combine images from different telescopes?”
Both is possible and the StarAlign process in PixInsight will take care of that. The key is the Reference Image: all other images will be aligned (and resized!) to match the stars in the Reference Image. So you should make sure that an image with the shortest focal length (in my case one of those from the first night) acts as the reference – that will shrink the other images (whereas doing it the other way round would “enlarge” the images from the first night, creating unwanted artifacts.
In my case, the StarAlign process took exactly 6 Minutes but only 64 images aligned. Why?
In this special case, the reason for the failure to align was a failure to sort out the obviously unusable images first – this one failed on tracking, producing “star trails” which then failed the alignment process. Actually, this is a good thing because it sorts out “bad data”.
But there is a better way of doing that: the PixInsight process for the initial visual inspection is named Blink. It simply loads all the images and then “flips” through them, either automatically or manually.
As you can see from the video: there are good images, bad images and “not quite too bad” images in there. Usually, I would have done this before I aligned the images (saves processing time!) but now, we can also use Blink to examine the effects of the StarAlign process:
Did you notice the “distortions” some of the frames showed? And how the field of view shifted suddenly to an area of the image, showing a 45° turned image? That is what StarAlign does for you: it aligns the images, rotates them where required and resizes them as needed. After a bit of clean-up (removing the distorted frames) this is what we are left with:
At the end of the day, our “good enough to stack” images turn out to be some 58 frames out of 91. Did you notice the satellite trails on some of the frames? I mentioned that ImageIntegration is taking care of these later but let’s first stack the images without and rejection algorithm:
Not horrible, but also not what we want – let’s do ImageIntegration again with what is called the “Sigma Clipping” rejection algorithm.
Now, ImageIntegration is producing three results – let’s look at the rejection map first (high-clipping):
The High-clipping Rejection Map shows all information that was not integrated into the final image based on the algorithm – you can clearly see the satellite trails here but also some of the “fuzziness” around the stars.
The second rejection map – the “Low-clipping” – can be used to crop the image later. It very clearly shows which areas of the image are covered by all stacked frames and which ones are not.
Last but not least the integrated image:
Before we continue with any other activitiy, I am goind to crop the image to the area of interest just around the four galaxies visible in here:
Why cropping now and not later? Because all other operations will a) be faster on a smaller image and b) when it comes to working with averages across the image, the algorithms will just include data that also remains in the final field of view.
Now that we got the stacked and cropped image, the first thing that should be done is to PlateSolve it. The ImageSolver in PixInsight needs to know some RA and Dec Coordinate that is within the image but in this case, it is easy: M81 provides the required information.
It always pays off to have a look at PixInsight’s Process Console window:
Here, we are getting some valuable information about the image:
The Resolution (3.397 arcseconds per pixel)
The Rotation (91.371°),
The Observation Time (taken from the first and last stacked image)
The calculated Focal Length (228.28 mm)
The Field of View, and
The Image Center coordinates as well as the corner coordinates
If you can platesolve the image, you can annotate the image:
The rest is “cleaning & adjusting” – in the following order:
Photometric Color Calibration
And if one wants, PhotoShop and some additional filters can also be applied, all a matter of “taste”.
So, last thing to do is some information just for reference – first, the finding chart so you know where in space you need to look at:
Then, some information on the four galaxies contained in this image:
Messier 81 (also known as “Bode’s Galaxy”) is a grand spiral galaxy some 12 million light-years from us. It measures roughly 90.000 light-years across.
Messier 82 (also know as “Cigar Galaxy”) is a starburst galaxy of approx. 37.000 light-years diameter.
NGC2976 is also a spiral galaxy, approx. the same distance than M81 and M82
NGC3077 is a small irregular galaxy, also approx. 12 million light-years from us.
All four galaxies are members of the M81 group which contains total of 34 galaxies in the constellations Ursa Major and Camelopardalis.
After my initial attempts at M81 (and missing my target), I had a second attempt just a few days later on May 16, 2020. Again, the Camera in use was my Nikon D90 with a Nikkor Zoom Lens set to 135 mm.
This time, the target was the southern region of Leo, specifically the area where I assumed the “Leo Triplet” to be. The “Leo Triplet”, that are three galaxies very closely together: Messier 65, Messier 66, and NGC 3628.
This time, my aim was spot on, which is not too difficult since a bright star, Theta Leonis (also known as “Chertan”) was a good aiming point. And this is the annotated version:
Zooming in to a 1:1 ratio, this time, the structure of the spiral galaxies becomes “visible” (though you still need a good idea of what you are looking at) – but again: just a DSLR and a 135 mm lens.
If you want to try for yourself – here is the finding chart: