In at the deep end – An introduction to imaging with a peculiar galaxy ARP 227 and a 1m telescope (1/2)

By: Mark Seaton, Flamsteed Astronomical Society

I signed up for the HOYS-LCO project when I heard about it on the Stargazers Lounge forum (SGL). It sounded very interesting and I was looking for something more from my new hobby – something to get my teeth into and to perhaps help justify to myself all the money I was spending on it! Not that hobbies really need justifying but… It has been interesting getting to know how the image capturing works using the remote 0.4m LCO telescopes and learning how to input and calibrate the captured data. I got a bit lost with actually analysing the light curves searching for variable stars but hope to revisit this and do some proper science with it!

When the Christmas picture competition was announced, I thought it would be fun to enter, and that it would be a good introduction to image processing which I had never done before, having only been interested in observing up until then. This meant learning the basics of image processing using a free software called Siril and processing my first ever astro-image using the data we had captured of IC5146, the Cocoon Nebula. It took a while and a lot of reading and YouTube videos but I have come to really like Siril.

I could not believe it when Dirk contacted me shortly after Christmas and told me I had come second place. Surely, there had been some mistake? However, what an opportunity. The prize was one hour of imaging time for any target I chose on  one of the 1 metre LCO telescopes in some exotic location with great skies. Wow!

The LCO 1m telescopes are fitted with LCO’s own design and build “Sinistro” camera. The telescopes have a focal length of 8000mm (calculated) so f8, and the sensor size of the camera is 4K x 4K with 15um pixels (60mm x 60mm) giving a field of view of 26.5 arcminutes x 26.5 arcminutes, and an image scale of 0.389 arcseconds per pixel. By normal standards, this is oversampled. The usual recommendation for amateur telescopes is 1-2 arcseconds/pixel as seeing is rarely better than that. The Sinistro camera utilises a Fairchild CCD486 CCD sensor cooled to -100deg C to minimise thermal noise. From the data sheet for the camera: “The imaging area is electrically divided into four quadrants. Each 2048 x 2048 segment may be clocked independently or combined as required.” Each quadrant has its own amplifier and it seems that the Sinistro may be reading out each quadrant individually in parallel for speed, but with the unfortunate result that minute differences in the amplifiers led to visible differences in the quadrants in my image (see below).

The LCO 1m telescopes are located all around the world. They have two in Siding Spring, NSW Australia (COJ), three in Sutherland, South Africa (CPT), three in Cerro Tololo, Northern Chile (LSC), and two in McDonald, Texas (ELP). You do not get to choose your telescope and not all of them are available all the time. When you submit a request, the scheduler automatically selects the best available telescope for the target and date you have requested. My images came back with a suffix LSC fa15, which identifies the telescope as one of the Cerro Tololo scopes. The Cerro Tololo observatory is located at an altitude of 2,207m.

The target ARP227

I thought about what to image long and hard, wanting to attempt something worthy of the aperture and something I would find a struggle with a smaller telescope. I chose ARP227, a group of unusual looking galaxies in Pisces, catalogued by Halton Arp in his Atlas of Peculiar Galaxies. I had seen an image of ARP227 taken with the 3.58m Canada-France-Hawaii Telescope on Facebook and thought it looked fascinating. Multiple swirling shells of dust and stars, very dynamic and unlike anything I had seen before.  It seems to be an unusual target for amateur imaging, as I could not find many examples on Astrobin or forums like SGL. However, in 2014, there was a supernova in NGC474, the main galaxy, and so as luck would have it there were many images in the LCO archive of this region. Most of these were short exposures and mainly in UV and IR and I did not get very good results trying to process them into a colour image. However, they did give me an idea of what I could expect. I hoped for much better.

A description from NASA’s APOD image of ARP227 by the Canada-France-Hawaii Telescope: “ExplanationWhat’s happening to galaxy NGC 474? The multiple layers of emission appear strangely complex and unexpected given the relatively featureless appearance of the elliptical galaxy in less deep images. The cause of the shells is currently unknown, but possibly tidal tails related to debris left over from absorbing numerous small galaxies in the past billion years. Alternatively, the shells may be like ripples in a pond, where the ongoing collision with the spiral galaxy just above NGC 474 is causing density waves to ripple through the galactic giant. Regardless of the actual cause, the featured image dramatically highlights the increasing consensus that at least some elliptical galaxies have formed in the recent past, and that the outer halos of most large galaxies are not really smooth but have complexities induced by frequent interactions with — and accretions of — smaller nearby galaxies. The halo of our own Milky Way Galaxy is one example of such unexpected complexity. NGC 474 spans about 250,000 light years and lies about 100 million light years distant toward the constellation of the Fish (Pisces).”

Unfortunately, my excitement to try such an impressive target blinded me to its inappropriateness and the problems I would have with it. The main problem was that it does not really get very high in the sky for any of the locations of the LCO telescopes and was particularly low during most of the prize execution period. It is also quite faint and to do it justice, I think it really needs more time than one hour even with 1m of aperture.

Setting up and taking the observations

I used Simbad to get precise coordinates for the target. I zoomed the viewer window to the field of view of the camera and panned the image to frame all the interesting parts that make up this ARP group and noted down the coordinates RA 01:19:44.4 DEC 03:21:21.6 (J2000). I did not need to worry too much about field orientation as the camera sensor is a perfect square and so long as I had the coordinates of the centre of my chosen framing, everything should fit nicely. This proved quite accurate.

In order to use as much of the one hour of time as possible, I set up three exposures in each of the B, V, and R filter. Each sub-frame had an exposure time of 280 seconds. Additionally I took three images with 200 seconds exposure though an ‘air’ filter, which I thought was a Luminance filter – but more about this later. My images were captured on the 22nd of July 2021 at approximately 9-10 UTC (5-6am local time). At this time, my target was about as high as it would get from Cerro Tololo at about 52degrees, which is not too bad, and the Moon and the Sun were below the horizon, but only just.

Using Siril to process the data

It took a while to become familiar with Siril but I have now worked out a workflow to process the images:

  • First go through the sub images using a FITS viewer and reject any that are especially poor – bad tracking and elongated stars, poor SNR (washed out background) etc.. I did not have a lot of choice here as I had only three subs per filter. They were all OK apart from a couple of satellite trails that I could not really reject without losing a large proportion of my data.
  • Load each colour sequence into SIRIL, convert and register.
  • Perform background extraction on the whole sequence (remember to tick the box for that!) This is useful for imaging like this at low altitude where the sky has a severe gradient and can change from sub to sub. In addition, this is useful if the moon makes the gradients irregular.
  • If feeling particularly thorough and if you have many subs, look at the Plot tab and delete any outliers before stacking. I could not do this with my data as I did not have enough to be choosy.
  • Stack using Average Stacking with Rejection and Additive with Scaling normalisation and use Linear Fit Clipping for rejection.
  • Repeat for other filter sequences
  • Load colours into RGB compositor
  • Align
  • Perform photometric colour calibration – great for getting truthful star colours. This adjusts the overall colour balance between the colour channels based on photometric data from the APASS/NOMAD star catalogues.
  • Crop if needed to remove any uneven borders caused by the alignment. This is important to do before further background extraction I think.
  • Perform ARCSINH stretch – sometimes needs several iterations before results start to appear but using this before Histogram stretch helps preserve true star colours set by the photometric calibration. There are two sliders – one for the stretching and the other to adjust the black point. I adjust the stretch until the image starts to lighten then dial it back with the black point slider and repeat until details start to show.
  • Perform Histogram stretch – but do not stretch too far! Too much stretching results in too much background noise coming through. I use the auto stretch button that always seems to go too far then scale back with the three sliders.
  • Perform background extract again if necessary.
  • Perform banding reduction if needed – this almost totally removed the quadrant tiling caused by the sectorised sensor used here. This can also be used pre-stacking and I am experimenting with this.
  • Perform Remove Green Noise. This often results in a magenta cast to the image but there is a trick to nulling that – invert the image and repeat the Remove Green Noise that has now effectively become remove Magenta noise. Then invert the image back to normal. This usually works well.
  • Median filter if desired to smooth background noise but beware, it softens everything!
  • Sometimes the Contrast-limited Adaptive Histogram Equalisation can be used to bring out very faint parts but it seems quite destructive so needs to be used carefully. I did use it on this data and it helped bring the shells out a little more.
  • Save as PNG and JPG and if wanting to revisit, FITS
  • Load RGB image into Gimp, tweak colour saturation, and colour temperature – it usually seems to need tweaking towards the blue. Adjust contrast and aim to darken background a little but not too much as it usually shows darker in other applications when viewing later.

Read in the second part about some of the issues encountered during the image processing. I will discuss how I have overcome them to create the final image that is shown on the top of the page.