The M87 Chain and the Pixinsight Zone System

One of the greatest euphemisms in the world has to be the phrase `learning experience'. How often do we sugar-coat our mistakes by calling them `learning experiences'? I'm sure I've done it many times. This image provides an example, but in this case there's a bit more to it than that...

A portion of the Virgo galaxy cluster, with the giant elliptical galaxy M87 at top left, and part of `Markarian's Chain' of galaxies at right. Click the image for a larger version, or click here for full size.

Data Acquisition: Making the best of a bad situation

A few weeks ago, I was doing some backyard imaging, and the Virgo galaxy cluster seemed like the logical choice. Having shot a luminance image of the Leo Triplet not long before, I decided to do another one-night stand, with just luminance, but this time I wanted to shoot `Downtown Virgo'. (The origins of that term and its enthusiastic usage seem to go back to Jay Freeman and Jamie Dillon, two highly-accomplished Bay Area visual observers.) Specifically, I wanted to shoot the portion of the Virgo cluster called Markarian's Chain. It's a standard target, since it comprises a pretty, arc-ing chain of galaxies that stretch from M84 and M86 towards M88. Almost everyone works on an image of Markarian's Chain at some point. By planning it out in SkySafari Pro 3 on my iPad, I could see that if I rotated my camera just right, I could frame most of the chain pretty nicely on my ST-8300 sensor, using my ED80 f/7.5 refractor.

One thought nagged at me, though... What about conventions? As in sign conventions and angle conventions? Sky Safari Pro 3 has a really nice slider tool for rotating the position angle of one's field-of-view overlay, relative to the sky. This allowed me to plan my framing really easily. And when I'm imaging, I can download a frame from the camera, and use MaximDL to plate-solve it, which gives me the image's position angle on the sky. This is really handy, but.... what if these two pieces of software use different conventions for specifying the position angle? Hmm. I could wind up with a frame that's rotated 90 degrees from what I expect.

So, it wasn't a great shock when that's exactly what happened. Here's the framing I had planned on my iPad:

Here's how things actually worked out, since the two pieces of software treated the position angle differently:

Hrm. Rargh. What to do? I could have rotated my camera 90 degrees, but that would mean refocusing and probably re-doing the GOTO alignment. Given the couple of hours available for shooting Downtown Virgo before it went behind some trees, I didn't want to do that. So, I panned around in SSP 3 and looked for an alternative framing. Here's what I wound up with:

That seemed like the best compromise, since it caught part of Markarian's Chain, and included the giant elliptical galaxy M87, the real `heart' of the Virgo cluster. I shot a couple of hours of luminance (in 5-minute subexposures), and called it a night.

Processing: Pixinsight meets the Astro Zone System

A few weeks later, I had a little time to sit down with the data, and after using the very handy new preprocessing script in Pixinsight, I saw the following preliminary result (this is a closeup of two of the galaxies in the Chain):

Autostretched image of two galaxies in Markarian's Chain.

It's probably worth explaining what I mean by an `autostretched' image (also sometimes called an AutoSTF'ed image amongst Pixinsight enthusiasts). PI has a tool called `Screen Transfer Function' (STF), which stretches the brightness values of the image's pixels, solely for the purpose of displaying the image on the screen. It doesn't change the original pixel values in the image file, but it basically creates a temporary copy of the image to display on the screen, with the brightnesses changed so as to make the dim parts of the image more visible. The STF tool has a `Auto' button, which creates an image that nicely shows `what you got'. (I used one of these AutoSTF'ed images in my annotated Leo Triplet posting.) Such an image, though, usually doesn't make for a very pretty picture, since it shows just how noisy the dim background areas and dim parts of your target look. That graininess is a combination of instrumental noise and the eponymous photon shot noise (the latter coming from both the target objects and from the sky.)

At this point, my big goal was to do some noise reduction, and try to make the noisy, grainy-looking parts of the image look a little better. In this I was aided by Jordi Gallego's new presentation on noise reduction in PI. There's a lot of good information in this document, but I was particularly intrigued Jordi's slides 51 through 53, particularly #53. In this slide, he shows that one can make masks for applying different noise reduction settings to different parts of the image, such as:

• The dark background sky, which has the lowest signal-to-noise ratio (SNR), and is thus the `grainiest'-looking part of the image.
• The dim parts of the deep-sky object(s), which have fairly low SNRs, and thus mostly need smoothing and noise reduction.
• The bright parts of the deep-sky object(s), which have high SNRs, and thus can tolerate some sharpening, such as through deconvolution.

Aha! This is basically the same concept as Ron Wodaski's Astro Zone System. I borrowed a copy of this book from a fellow Bay Area observer a couple of years ago, and found it to be very interesting. Sadly, the book has been out of print for some time, but I was one of the lucky folks at the 2011 Advanced Imaging Conference who managed to get one of the copies Ron gave away. (Thanks, Ron!)

After a little fiddling around, I realized that PI's Range Selection tool works best on images that have already been stretched into a nonlinear state, so I made a copy of the image, applied its AutoSTF settings to Histogram Transformation, and applied that to the copy. I then used Range Selection on this stretched copy.

First, I made a mask that covered up the stars and galaxies, leaving only the dark background sky to work on:

After a little fiddling around, I stumbled on some settings in Multiscale Median Transform that smoothed the background reasonably well:

I was pleased with this result! It's not perfectly smooth, but I'm calling this a win, so far. Then, I made a mask for the `mid-SNR' zone, which included the fainter outer parts of the galaxies:

And then, by pulling back on my MMT noise reduction settings, I was able to smooth those areas somewhat. Next I made a mask to isolate the cores of the galaxies, for sharpening via Deconvolution:

After mid-SNR-range smoothing and high-SNR-range deconvolution, I had this image:

The brightness levels you see here are `Auto-STF' levels, and even with the noise reduction, they're not really good for posting on the web. So, since the image was still at a linear stage (i.e. not really brightness-stretched yet), it was time for a Histogram Transformation, some star shrinking, and a horizontal flip to match the correct appearance of this area on the sky:

Room for Improvement:

I think this was a good proof-of-concept project, for the Range Selection / `Pixinsight Zone System' approach. My masks could use some work, though. When I examine the image closely, I can see that some of the dim parts of the galaxies got left out of the masking process. Also, the various processing steps left an artificial ring around M87. There really are such things as ring galaxies, but M87 isn't one of them. I'm very interested in refining my touch with Range Selection, and to trying out the new Adaptive Stretch tool! A week or so after shooting these data, I managed to shoot Markarian's Chain with proper framing, and so we'll see how things go with this new data set.

The (Leo) Luminance Triplet

For such a dry winter, California didn't have a lot of imaging-quality skies in early 2012. We had some late-season rain and mountain snow, which was good for our hydro balance, but not so good for the spring galaxy season. I finally got out in mid-May, and spent a couple of nights shooting M65, M66, and NGC 3628, otherwise known as the Leo Triplet. Here's the result, sized for a 15" MacBook Pro screen:

This is what's known as a `luminance' image, which means it was shot with a black-and-white (or `monochrome') CCD camera, through a clear (or `luminance') filter. In order to make a color image, I'll need to shoot it through 2 or 3 color filters. If all goes well, I hope to shoot it through Red, Green, and Blue filters before the spring season slips away. The subexposures for this image were each 5 minutes long, and I shot about 50 of them over two nights, for a total exposure time of about 4 hours. As always, the imaging scope was an Orion ED80 f/7.5 semi-apo refractor.

This was also the inaugural imaging run for my new (to me) Losmandy G-11 mount. I got a great deal on it from a fellow Bay Area imager, and I spent the April dark-moon period learning some of the ins and outs. I feel like I can polar align, acquire targets with the Gemini 1 (Level 4) goto system, and I can get pretty good autoguiding. During the nights when I shot these luminance frames, the RMS error on my guider corrections was running about 1/2 pixel in both RA and Dec.

I processed this image in Pixinsight, making use of the new Batch Preprocessing script. Very handy! Many thanks to the folks who wrote that script. Also many thanks to Mike Schuster for writing the PSF Estimation script, which auto-picked hundreds of stars and gave me the parameters of the point-spread function, which I used for Richardson-Lucy deconvolution. (Deconvolution is a sharpening routine that I used to bring out some of the details in the galaxies.) The hardest part of the whole processing workflow was the noise reduction, which I did with Multiscale Median Transform. Once I had the noise somewhat beaten down, I could get a halfway-decent stretched image from the Histogram Transformation. I did a bit of HDR Median Transform, but not nearly as much as I might use on, say, a large bright nebula.

I hope to be able to get out and shoot some RGB color data if I'm lucky; it would be nice to add color to these galaxies!

M33: Two nights at Dino

Here's M33, the Triangulum galaxy:

(There's probably an issue with orientation or `flipping' of the image, but since I've stared at it for so long in this orientation, this is becoming `how it looks to me'.)

This image has me thinking about two `themes':

1) The pleasures of imaging from a nice dark site, like Dinosaur Point.

2) The difficulties of getting good data on M33, the Triangulum Galaxy.

I shot these data on two successive Saturday evenings, October 22 and 29, 2011, from an observing site called Dinosaur Point. It's a boat ramp on the San Luis Reservoir. The reservoir is part of California's enormous system of water projects, which control floods, supply water, and supply electricity. One function of the San Luis reservoir is, essentially, as a giant electrical storage battery. Water gets pumped uphill into the reservoir at night, when electric rates are low, and the water is drained downhill (through generators) during the day.

Dinosaur Point has long been a favorite winter dark-sky site for Bay Area observers. It tends to be too windy during the warm months. But in the late fall and winter, if the `tule fog' from the nearby Central Valley hasn't covered it, Dino can be a very dark site. I really enjoyed setting up there and imaging M33; the sky was nice and dark. One night, in the wee hours of the morning, we even saw the adaptive-optics laser beam from Lick Observatory, shooting towards some object in the south.

It's very important to note, though, that observing access to Dino is subject to some very specific conditions. If you're a Bay Area observer who hasn't been there, make quite sure that you've read and understood the `gatekeeper' access protocol! You can also check the TAC list and the TAC Observing Intents page to see if a gatekeeper is going. Don't just go there without checking all of these details first!

I acquired these data with the same rig as the last couple of shots - my Orion ED80 refractor (80mm f/7.5) with the SBIG ST-8300M CCD camera. I shot unbinned luminance data, and 2x2 binned color data through R, G, and B filters. If I recall correctly, I think I have a couple of hours from each filter. That would make for 8 or so hours of total exposure time, give or take.

I think that M33 has some potential to be a frustrating object for beginning astro-imagers. Typically, I think a lot of us undergo a pattern like this: a) We get a CCD camera during the summer, and by autumn we have a basic understanding of how to use it. b) During the fall, we shoot M31, which is so bright that we can get a decent signal-to-noise ratio over most parts of the galaxy, without too much trouble. c) Next, we say to ourselves `Aha, look what's nearby - M33! There's another big bright galaxy just waiting to be shot!' As it turns out, however, M33 has a lower surface brightness than most of M31, and it's tough to build enough SNR to get a good image. Unless you're using an optical system with a very fast focal ratio, M33 is going to take a long time to build a decent dataset.

This dataset really isn't long enough, but I decided to go ahead and try to process it anyway. I probably won't be able to shoot M33 again until summer or fall 2012, so here's what I've got, so far. With a considerable amount of time invested in Pixinsight, I was able to get something semi-presentable.

Processing in Pixinsight:

I started with the usual calibration routine, using light, dark, bias, and flat-field frames, and I extracted the small amount of light-pollution gradient that one gets at Dino. This gave me linear (i.e. unstretched) luminance (L) and color (RGB) images. These images had the usual background-neutralization and color-calibration corrections applied to them. Then it was time to get a little more from the linear images. First, a bit of noise reduction using the Multiscale Median Transform tool. Then I used the new DynamicPSF module to build a model point-spread function for each image, and fed that PSF into a gentle application of regularized Richardson-Lucy deconvolution. This helped to bring out a bit more detail in the central part of the galaxy.

Then it was time to go non-linear with each image. I did this the easy way: For each image, I did an auto-STF (Screen Transfer Function), and applied each of those auto-STFs to instances of the Histogram Transformation tool. This gave me stretched images that had very similar histograms - and that's just what the LRGB combination tool wants.

If I recall correctly, I did a bit of SCNR (Selective Color Noise Reduction) to take out some of the `galaxy green' in the RGB image, before performing the LRGB combination. I increased the saturation a bit when making the LRGB image, and used Pixinsight's magic Chrominance Noise Reduction routine.

With the LRGB image in hand, it was time to perform two parallel lines of attack, which would later be combined:

1) Compress the dynamic range a bit with HDR wavelets, so as to take away some of the `over-bright dominance' (for lack of a better term) of the central part of the galaxy, and then punch up the contrast with Local Histogram Equalization.

2) Try my hand at the mystical `multiscale processing', a la Rogelio. I split a copy of the LRGB image into large-scale and small-scale components, following the general method of Rogelio's and Vicent's multiscale tutorials. I didn't to anything extra to the smallscale image; I just didn't have the mental energy. But I did some Histogram Transformation (and possibly HDRWT, IIRC) to the large-scale image, brightening the midtones and re-setting the black point. Then I combined everything back together with PixelMath:

a) The LRGB image
b) The LRGB image that had been HDRWavelets-ed and LHE-ed
c) The smallscale image
d) 0.25 * the stretched-even-more largescale image.

Following this recombination, I made a Star Mask (with default parameters), and used Morphological Transformation to dim/shrink the small and medium-sized stars. At that point, I said `Stick a fork in this sucker, it's done. Put it on the blog.'

Room for Improvement:

When I look at this image, it seems to me like it's still afflicted with a bit of `galaxy green', but when I applied an additional round of SCNR to it, it didn't seem to change. Some of the stars also wound up looking a bit pink, but at this point, I'm too tired to fight about it.

Next, there are the big, bloaty stars. These are the bane of all my images. My temptation is to blame them on the small aperture of my telescope. An 80mm scope will have a big, fat point-spread function, and if I want tiny stars, I'll need a bigger scope. That's probably true, to some extent, but I'll bet it's not the whole story. I am beginning to suspect that the big, halo-y stars are a consequence of the fairly severe stretching that the image has undergone. M33's dim, and it takes a lot of stretching. This probably brings the outer parts of the PSFs up to an objectionable brightness. With a longer total exposure time, I could probably get the faint parts of M33 to show up without as much stretching. (Of course, this raises the question of whether those outer portions of the PSFs would show up, too... hmm...) I'd love to figure out how to shrink those stars, so that it looks like I used a bigger scope. After a lot of fiddling around with Star Mask and Morphological Transformation, however, I haven't found a way. It remains a dream.

With more integration time, I think I could show more of the faint outer portions of M33. I'd love to get in night after night on this object, and really punch out every part of this galaxy. M33 is full of resolved stars and HII regions like NGC 604. I often think of M31 and M33 as the closest thing we've got the Magellanic Clouds up here in the NoHem, and it would be nice to make the deepest, sharpest images of them that I can.

Naturally, many people have gotten some very nice, very deep images of M33. One of my favorites is this one by Stephane Guisard, because he shot it from the Atacama region of Chile - exactly the `wrong' place to get a good image of M33. Shows you how good places like Paranal are! And of course, there's a nice Hubble image of NGC 604, the most prominent star-forming region in M33. (In my image, the way I've got it oriented, NGC 604 is down and to the right of the galaxy's center, above two prominent, bloated orange field stars.)

M31 2011

A major event for California observers is the yearly California Star Party, or `Calstar'. My Bay Area buddies and I look forward to it each year. In 2011, I worked on M31, the Andromeda galaxy. M31 is a classic autumn object, rising in the evening and riding high for much of the night. I'd spent previous Calstars observing it in detail visually, and this year I wanted to get the best possible RGB imaging data that I could.

Happily, I'd just taken delivery of a new SBIG ST-8300M CCD camera, and I was eager to try it out. (Many thanks to Sam Sweiss at Scope City for helping me get it! This also meant that I could give the QSI 583 back to my Cilice friend, enabling him to image at Calstar.)

SBIG ST-8300M and Orion 2" LRGB filter wheel

Like the Lassen run in which I imaged the Eagle nebula, this year's Calstar was blessed with good weather. I got in a solid 3 nights of clear, dark skies, and managed to get several hours each of unbinned R, G, and B images. Calibration, integration, and processing in Pixinsight gave me this image:

The Andromeda galaxy (M31), approx. 15 hours total exposure time

After talking about star shrinking in yesterday's blog entry, I went back to RBA's M31 star-shrinking tutorial, and worked the problem some more. The image above has had its `medium-sized' stars dimmed, following Rogelio's tutorial. As he pointed out, M31 is not in the plane of the Milky Way, and thus doesn't need a lot of star reduction, but I think it helps the overall appearance of the image.


Room for Improvement:

I'm fairly pleased with the star shrinking / reduction / whatever you want to call it, but I need to double-check that I haven't affected the starlike nuclei of M31, M32, and NGC 205 too much. I also really want to figure out how to reduce the brightest and most bloated stars, like the blue one that appears to the lower left of M32, and the orange one that appears to the upper left of M32. As I stretched the image, these got so big, their halos make them look like `candidate satellite galaxies'. I still haven't figured out how to make a star mask that isolates only the brightest stars.