Animation – Movement of Comet 41P

The word “planet” comes from the Greek work “planan” which means to wander. Early star gazers noticed that some bright stars moved with respect to other fixed stars.  Those bright stars are our closest planets: Mercury, Venus, Mars, Jupiter and Saturn. Comets also move a fair bit across the sky, but the origin of the word has more to do about stars “with long hair” than it’s traveling behavior.

Last weekend I managed to photograph comet 41P//Tuttle–Giacobini–Kresák, and I identified in my blog that it’s movement was visible frame to frame. Well I’ve finally gotten around to create a small animation of that movement. For those wondering what’s the comet’s velocity, it’s currently travelling at 37.4 km/s.

Animation of comet 41P/Tuttle–Giacobini–Kresák (45 minutes)

Animation of comet 41P/Tuttle–Giacobini–Kresák (41 minutes)

The above is composed of 32 frames, each a 1 minute exposure spanning a time of 41 minutes. You are probably thinking “it should be 32 minutes, not 41!”. That is because I have a delay between each frame to allow the camera to send the photo to the computer. Hence between the first and last frame, 41 minutes have elapsed.

Jupiter and Three Moons

Started processing some of the images taken on April 8th, the only evening with a clear night. I spend a good hour in the near freezing air to capture Jupiter with various settings. The one below was taken with a 2X barlow and a simple webcam. This is a mosaic of two frames as not all moons fit into the rather narrow 640×480 CCD sensor. Unfortunately the fourth moon, Callisto, is just out of the frame to the right.

Jupiter - 2017 opposition - SW80ED and 2x barlow

Jupiter – 2017 opposition – SW80ED and 2x barlow

Telescope: Skywatcher 80ED with 2x barlow lens
Sensor: Philips Vesta webcam with IR-UR cut filter
Processing: Registax and GIMP

Took 40 seconds of video at 20 images/sec which produced a 351MB AVI file. The video is then analysed, registered and stacked with Registax.  Color saturation and light levels where then adjusted in GIMP.

I also took many more video with a 3x barlow, but getting the focus right was a challenge. And I’m afraid the end result is just a “bigger” Jupiter, no additional details. I will need a few nights to process those and see which one turned out well. I will also try using the drizzle algorithm on the image above to see if I can get a larger and better image.

Lower Orion Constellation

Just when you think you have a good “recipe” to process astronomy images taken with your gear, things don’t quite work out and you end up spending three evenings trying different settings, techniques and steps because you know there’s a better image waiting to be teased out.

M72 and Lower Orion Constellation

M72 and Lower Orion Constellation – Benoit Guertin

The image above (click for a full frame) is as much as I can stretch out from the lower half  of the Orion constellation and nebula with a 20 seconds ISO 800 exposure on 85mm F5.6 Canon lens from my light polluted backyard.

Below is the sky chart of the same area showing the famous Orion Nebula (blue and red box) and the Orion belt with the three bright stars Alnitak, Alnilam and Mintaka.  What is unfortunate is there are lots of interesting deep space nebula structures that glow in the hydrogen-alpha spectral lines of near infra-red, but all photographic cameras have IR filters to cut on the sensor those out.  That is why many modify the cameras to remove the filter, or get dedicated astro-imaging cameras.

Sky Chart - Lower Orion with nebula and open star clusters

Sky Chart – Lower Orion with nebula and open star clusters

Now, back to the main topic of trying to process this wide field image.  I had various issues with getting the background sky uniform, other times the color just disappeared and I was left with essentially a grey nebula; the distinctive red and greenish hue from the hydrogen and oxygen molecules was gone.  And there was the constant hassle of removing noise from the image as I was stretching it a fair bit.  I also had to be careful as I was using different software tools, and each don’t read/write the image files the same way.  And some formats would cause bad re-sampling or clipping, killing the dynamic range.

Below is a single 20 seconds exposure at ISO 800.  The Orion nebula (M72) is just barely visible over the light pollution.

orion_2017-02-27_original

Original image – high light position for 20 seconds exposure

The sky-flog (light pollution) is already half way into the light levels.  Yes, there are also utility lines in the frame.  As these will slightly “move” with every shot as as the equatorial mount tracked I figured I could make them numerically disappear.  More on that later…

Light levels of a 20 second exposure due to light pollution

Light levels of a 20 second exposure due to “sky fog”

The longer you expose, the more light enters the camera and fainter details can be captured.  However when the background level is already causing a peak mid-way, longer exposures won’t give you fainter details; it will simply give you a brighter light-polluted background.  So I needed to go with quantity of exposures to ideally reach at least 30 minutes of exposure time. Therefore programmed for 100 exposures.

Once the 100 exposures completed, I finished with dark, flat and offset frames to help with the processing.  So what were the final steps to reach the above final result?   As mentioned above, I used three different software tools, each for a specific set of tasks: DSS for registration and stacking, IRIS for color calibration and gradient removal and finally GIMP for levels and noise removal.

  1. Load the light, dark, flats and offset images in Deep Sky Stacker (DSS).
  2. Perform registration and stacking.  To get rid of the utility lines as well as any satellite or airplane tracks, the Median Kappa-Sigma method to stack yields the best results.  Essentially anything that falls out of the norm gets replaced with the norm.  So aircraft navigation lights which show up only on one frame of 100 gets replaced with the average of all the other frames.  That also meant the utility lines, which moved at every frame due to the mount tracking, would vanish in the final result.
  3. As my plan is to use IRIS to calibrate colors, where I can select a specific star for the calibration, I set the no background or RGB color calibration for DSS.
  4. The resulting file from DSS is saved in 16-bit TIF format (by default DSS saves in 32-bit, but that can’t be opened by IRIS).  I didn’t play around with the levels or curves in DSS.  That will be dealt later, a bit in IRIS, but mostly in GIMP.
  5. I use IRIS to perform background sky calibration to black by selecting the darkest part of the image and using the “black” command.  This will offset each RGB channel to read ZERO for the portion of the sky I selected.  The reason for this is the next steps work best when a black is truly ZERO.  While IRIS works in 16-bit, it’s actually -32,768 to + 32,768 for each RGB channel.  If your “black” has an intensity of -3404, the color calibration and scaling won’t be good.
  6. The next step requires you to find a yellow Sun-like star to perform color calibration.  As a white piece of paper under direct sunlight is “white”, finding a star with similar spectral color is best.  Sky chart software can help you with that (Carte du Ciel or C2A is what I use).  Once located and selected the “white” command will scale the RGB channels accordingly.
  7. The final step is to remove the remaining sky gradient, so that the background can be uniform.  Below is the image before using the sky gradient removal tool in IRIS.
  8. Image before removal of sky gradient in IRIS

    Image before removal of sky gradient in IRIS

  9. Once the sky gradient is removed, the tasks in IRIS is complete, save the file in BMP format (will be 16-bit)  for the next software: GIMP
  10. The first step in GIMP is to adjust light curves and levels.  This is done before any of the filers or layer techniques is performed.
  11. Then I played around with the saturation and Gaussian blur for noise reduction.  As you don’t always want the transformations to take place on the entire image, using layers is a must.
  12. For the final image above, I created two duplicate layers, where I could play with color saturation, blurring (to remove the background noise) and levels until I got the desired end result.  Masks are very helpful in selecting what portion of the image should be transparent to the other layers.  An example is I wanted a strong blur to blend away the digital image processing noise, but don’t want a final blurry night sky.

Processing RAW Cassini Spacecraft Images

Did you know that you can get access to the latest RAW images from the Cassini spacecraft directly from the NASA and JPL website?  Not only will you have first look at some stunning images of Saturn, the rings and the Moons like this one below from January 16th.  Click the image below for more information from NASA/JPL on that specific photo.

Daphnis making waves - Cassini spacecraft Jan. 16, 2017 - JPL/NASA

Daphnis making waves – Cassini spacecraft Jan. 16, 2017 – JPL/NASA

But you can also download raw images to try your luck at processing.  For this exercise I selected these series of pictures of the strangely perfect hexagonal-shaped storm on Saturn’s north pole.

Downloaded raw image set

Downloaded raw image set

These are images taken with different filters by the wide field camera, and I noted in an Excel file some information on each image, most importantly which filter was used.  Both the narrow and wide CCD on Cassini operate with two filter wheels, hence each image will always list two filters.  For those surprised at the rather “small” 1 mega-pixel camera, keep in mind the spacecraft was launched nearly 20 years ago, and development started in the 1980s.

There is a very detailed document on how to use, calibrate and process the images found at the following link.  But for what I wanted (quick processing) I only needed to find out which filters were the closest to an RGB setup.

Cassini ISS Broadband Filters

Cassini ISS Broadband Filters

Luckily this is well documented, and found them with the BL1, RED and GRN filters.

The image below is a quick addition of those 3 respective images assigned to red, green and blue channels.  The resulting image would be somewhat near the real colours, but I did not take any time to calibrate, hence they are probably a little off…

Saturn with normal RGB assignment (close to real colours)
Saturn with normal RGB assignment (close to real colours)

I also decided to try something that would provide a little more contrast and dive a little into the atmosphere and went with a IR-Red-Blue for RGB assignment by using a one of the narrow-band filters.

Cassini ISS Narrow Band Filters

Cassini ISS Narrow Band Filters

Saturn with IR, Red and Blue for RGB assignment

Saturn with IR, Red and Blue for RGB assignment

Both images above have not be calibrated, stretch or adjusted other than combine the raw images from Cassini.

The NASA/JPL site even has a section for amateurs to submit their photos and host a gallery to see what others have done.

References:
Cassini NASA/JPL site
Cassini Imaging Science Subsystem (ISS) Data User Guide

DeepSkyStacker – Faster and Better Results (updated)

Tried DeepSkyStacker and I think I’ve found a better and faster way of processing my images.

I had been using IRIS for the better part of the last 6 years, and I remember how impress I was at the results compared to the early versions of Registax for deep sky images.  While  IRIS is quite manual and command-line based, it nevertheless got the job done and allowed me to experiment with different methods.  But now, I decided it was time to move on to something a little modern.  I looked at what others were using, and came across DeepSkyStacker.

DeepSkyStacker

While IRIS offers a complete package, from image acquisition, pre/post-processing, and analysis tools; DeepSkyStacker only performs the registration and stacking.  But it does so in a faster and more efficient way.  DeepSkyStacker can fully utilise RAM and multi-core processing; hence what took 30 minutes in IRIS is now down to 5 minutes in DeepSkyStacker.

It also automates many steps, and you can even save the process and create batches.  So it’s down to load all your files, and then one click to register and stack.

DeepSkyStacker - Processing Files

DeepSkyStacker – Processing Files

I tried the with some wide field of views I had taken back in September.  And the resulting image appeared to be better.  Now I still have to use IRIS as I like how it can remove the sky background gradient and adjust the colors.  And GIMP is still required for the final adjustments.  So here are the main steps that gave me good results:

  1. Load the light, dark, offsets and flat frames (I had no flats or bias/offsets in my trial run, but that didn’t appear to cause an issue)
  2. Ensure that all pictures are checked and select to Register the checked pictures
  3. For the stacking, I found that selecting RGB Channels Background Calibration provided good color, and used the Kappa-Sigma clipping to remove noise.
  4. After stacking DSS will create an Autosave.tif (32-bit TIFF file).  I need to convert this into another format, but without loose the dynamic range.  My current solution is to use Microsoft Photo Gallery to open and save another copy as JPEG.  Finally did a quick stretching of the RGB levels to ensure better dynamic range when saving to 16-bit TIFF.  16-bit TIFF appears to be the only one that will open correctly in IRIS.
  5. Once in the image loaded in IRIS to remove the background sky gradient.  And then save it in BMP format for import into GIMP.  Yes I know I another file format, so far it’s what I find works best.  GIMP converts FITS and TIFF to 8-bit, causing incorrect color depth.
  6. Final adjustments with levels, light curves, saturation, noise filtering, etc.. is done in GIMP.

Now for a little more playing around, and trying it on some on my older pictures.

UPDATE:
DeepSkyStacker saves files in 32-bit TIFF by default.  After stacking many images the dynamic range is quite large, and this is not data we want to loose.  But the problem was finding a program that was able to correctly handle the 32-bit file format.  The next release of GIMP (version 2.10) will handle 32-bit files, but GIMP 2.8 was limited to 16-bit and even there it would convert the image to 8-bit for manipulation (GIMP 2.9.2 and up might work, but needs to be compiles on your computer – development package).  Not good…  Before downloading yet another photo imaging software I tried some of my current programs and found that the  Microsoft Photo Gallery software for Windows 10 does a great job of handling the 32-bit TIFF files.  Once the image opened, under File – Make a Copy I save a version in JPEG.  Yes I know not ideal, but I avoid a lot of the quantization conversion error and I’m able to continue my processing in IRIS and GIMP.

 

Layers and Blurring

Image

We spend lots of money on expensive optics and hours trying to get the focus spot-on or the mount alignment/guiding perfect for smooth tracking to avoid blurry and stretched stars.  So why would you want to blur your final image?

Consider the images below.  The one of the left is softer and more pleasing to the eyes, yet the stars remained sharp.

blurredlayers_compare

Side-by-side compare of blurred and the original image

One way to obtain this effect is by creating copies of the image, applying varying blur to each and then adding them from heaviest to the least blur using the Lighten only layer mode.

Take your original image and duplicate as required (in my example I blurred two layers, hence need a total of three identical layers).

blurredlayers_original

Original image (centered on Constellation Vulpecula)

Apply heavy blur to the bottom layer.  At the same time, reduce the color saturation and adjust the levels to get nice blacks.  You want the blacks to be nice and dark such that the general shape of the cloud-like structures appear due to the bright and dark zones.  In this example, the blur was applied to a level of 80 pixels.

blurredlayers_bottom

Heavy blur to the bottom layer, and reduced color saturation

Repeat the same for the middle layer, but with less blur (level of 20 pixels).  If you want the colors of the stars to pop out, increase the color saturation.  It will create an effect of nebulosity around bright stars.  Once again, adjust the levels as required.

blurredlayers_mid

Medium blur to create nebulosity effect

Finally, the top layer don’t apply any blur, adjust the curves to reduce the faint portion of the image as you don’t need to keep this portion of the image.  You only want to keep the nice bright stars.  The dim structures are kept in the lower two blurred layers.

Adjust the % between the layers to get the desired effects  The pixel intensity from bottom (most blurred) to the top will be kept only if the result is brighter than the previous layer.  The sharp and bright stars are from the top layer, while the overall dim structures are from the blurred lower layers.

blurredlayers

Final result after blending the 3 layers

Turn the various layers on/off to see what is the contribution of each.  It’s a lot of trial and error depending what you accentuate versus what you want to fade into the background.  Play with the level of blur, the curves and the % layer blending until you get the effect you desire.

For more information on the original image, see my post on Vulpecula.

Moon – Not Waiting for Dark Skies

Image

There’s no need to wait for dark skies to observe and photograph the Moon.  Actually most backyard astronomer don’t like the Moon as it just adds to the light pollution and prefer observing when it’s not around.

But as the Sun is setting and you’re getting your gear out, it’s hard not to take a few moments to swing the telescope over and observe the Moon.  I find the Moon so bright during the night that it almost blinds at the telescope, hence observing it under still blue skies is a great way to observe details without having to squint under darkness.  The photo below as taken at 7pm, still not under dark sky conditions.

April 15th, 2016 Moon - Benoit Guertin

April 15th, 2016 Moon – Benoit Guertin

Skywatcher 80ED
Canon 400D (ISO 400) 1/800sec
Processing with Registax6
Adding wavelet and non-wavelet layers with GIMP

The wavelet processing in Registax greatly increased the finer details on the Moon, however it also increased the noise in the blue sky background.  Therefore I opened both the pre and post wavelet pictures in GIMP and created a mask such that on the wavelet layer, only the lunar surface passed.  This was done by creating a mask based on alpha (luminance) and using BLUR to flag the entire Moon as my area of interest that I wanted to pass through.