From the Pros: Multi-wavelength Eagle

When I say `the pros', what I'm really talking about are research astronomers. These are the folks who do fundamental research in astronomy, such as the people who make observations with the Herschel infrared space telescope and the XMM-Newton X-ray space telescope. Most of these big-buck research projects are pretty good about remembering the public outreach part of their mission. Here's an example: Today's NASA Image of the Day is a view of the Eagle nebula, captured in two very different wavelengths - infrared and x-ray:

(Image credit: ESA/Herschel/PACS/SPIRE/Hill, Motte, HOBYS Key Programme Consortium)

Having recently spent so much time on processing the Eagle nebula, it's fun to see it in wavelengths that I can't capture with my CCD camera from the Earth's surface.

Naturally, I can't resist including the most famous `pro' shot of a part of the Eagle nebula:

(Image credit: NASA / STScI / Hubble Heritage Team)

I'll bet you've seen this image before. It was acquired by the Hubble Space Telescope in the 1990s, and has been very widely reproduced and distributed. It's probably one of the most famous `Hubble shots' of all time, if not the most famous. (I'll take a moment here to plug a friend's business, where you can buy prints of the Pillars.)

If you look closely in the Herschel / XMM-Newton image, and even in my Eagle image, you can make out these pillars. In fact, they're even visible to the eye, if you use a reasonably large telescope, and you're observing from a very dark site under good conditions. When I've taken my 18" (45cm) scope to observing sites in the northern California mountains in the summer, I've sometimes been able to make out the two largest pillars from the image above. It's tough, but with some practice, an OIII filter, and careful examination of a printed image (using very dim red light, so as not to spoil one's dark-adaptation), they're just visible. It's fun to be able to see something so well known with your own eyes! It's fun to be able to capture it with one's own telescope, too.

UPDATED a couple of hours later...

The Herschel and XMM-Newton missions are run by the European Space Agency, and they've got a nice webpage about these multi-wavelength observations of the Eagle nebula. It includes a video showing the various images and how they correspond to each other. Here's a summary image, which places the various Eagle images next to each other:

(Image Credit: European Space Agency, European Southern Observatory, NASA)

One of my favorite of the `Pillars' images is the near-infrared image; it's the center image in the right-hand column of the mosaic above. It was acquired using one of the giant 8-meter telescopes of the Very Large Telescope observatory at Paranal, Chile. I love the purple color palette of this image:

(Image Credit: VLT/ISAAC/McCaughrean & Andersen/AIP/ESO)

The team that made this image used an infrared camera/spectrograph called ISAAC to collect image data in three wavelength bands, all of which are in the infrared. This means that the wavelength of the `light' in each band is longer than that of visible light - it's beyond our eyes' ability to see. The dust that makes up the Pillars is mostly opaque at visible wavelengths, but infrared `light' can make it through a greater thickness of dust than visible light can. As a result, they can see deeper into the Pillars, or entirely through them in the case of the left-hand pillar. This allows for a clearer view of young stars that are forming out of these clouds of gas and dust.

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.)

Eagle nebula in B&W H-alpha

Ever since this summer's imaging session at Lassen, I've wanted to process the hydrogen-alpha data that I acquired as a black-and-white image. I spent this evening working on the data in Pixinsight, and here's what I've come up with so far:

Acquisition:

I shot these data during two nights, using 15-minute subexposures through an Astrodon 3nm H-alpha filter, for a total exposure time of 5 hours. This was with the 80mm refractor and borrowed QSI camera that I described in a previous post.

I've always enjoyed the look of black-and-white hydrogen-alpha images, and I wanted to try and make one myself. Images like this remind me of the days of heroic long exposures on gas-hypered Technical Pan 2415 film... days that I have to admit I didn't experience first-hand. And, frankly, I'm not too sorry about it, although it would make for some nice bragging rights. Me, I'm grateful for CCD cameras and autoguiders, which make the whole thing a lot more do-able, although it's still a fair amount of work.

The real key to an image like this is the narrowband hydrogen-alpha filter. I'm lucky that my friend from Cilice, who loaned me the camera, had invested in a filter with such a narrow bandpass. Besides bringing out all of the lovely emission nebulosity (which would look deep red in a color image), a filter like this makes the stars look very small! That's a very nice `perk', although it makes focusing and framing the image rather time-consuming. No need to shrink the stars in software when you have such tiny stars to begin with! I can't wait to get an H-alpha filter for my SBIG filter wheel, someday. I think I'll go with 3nm - it's worth the extra effort.

Processing in Pixinsight:

Like most CCD image processing, part of my workflow happened while the image was still linear, and then I took it to the non-linear realm with a histogram stretch, where I did further processing.

I started by using the A Trous Wavelet Transform (ATWT) tool to reduce noise, following the example from Juan Conejero's `tutorial post'. I used considerably less aggressive ATWT noise-reduction settings than Juan's example, though. Then I did some Richardson-Lucy deconvolution, again following a tutorial-like post by Juan. A real key to getting Deconvolution to work is the use of Dynamic PSF to model the telescope's point-spread function.

Once I had reduced noise with ATWT and applied a bit of deconvolution, I stretched the image into the non-linear realm using Histogram Transformation. (I just applied the stretch parameters from an AutoSTF into HistoTrans.) As per usual Pixinsight practice, I used the HDR Multiscale Median Transform (formerly HDRWT) to bring down the brightness in the central part of the nebula. I found that increasing the number of wavelet layers to 8 helped bring out detail nicely, and did the best job of `taming' the brightest areas. I did another moderate histogram stretch to increase contrast, and then applied the Local Histogram Equalization (LHE) tool, with a contrast limit of 2.0 and and Amount of .25.

A last, light little shot of ACDR was the last step. I did this with the built-in lightness mask enabled, so as to apply it only to the darkest areas. These areas had had their noise increased a bit by LHE.

Assessment:

I'm reasonably pleased with how this image turned out. I like the way the deconvolution brought out detail around the `Pillars of Creation' and other dusty structures in the nebula. HDRMMT also helped to bring out a fair amount of detail, and LHE pumped up the contrast between adjacent light and dark areas.

Naturally, I'd love to get additional hours of data, to bring out even more nebulosity at a reasonably high signal-to-noise ratio. Maybe next summer!

Oh, I almost forgot: I flipped the image left-for-right, compared to my previous Eagle nebula image. I hadn't realized that the previous image was oriented incorrectly. I think this one matches the published `Pillars' images better.

Hmmm... I wonder... since LRGB combinations in Pixinsight are supposed to be assembled from non-linear images, I wonder if I could get the histogram of the RGB image into the right kind of shape to match this one, and use this B&W H-alpha image as the luminance for an LRGB combine?  Hmm... I ought to check that out.