After spending ample time studying and imaging our nearest celestial neighbor, the Moon, it's only natural to widen our view to the remainder of our nearby group, our solar system. Specifically, the eight planets of our solar system in full color.
I will present my images in all of their glory plus the acquisition process together.
Unfortunately, not every planet was visible but I was able to capture data for Mars, Jupiter, Uranus, and Neptune. Let's dive in! 🤿
Let's begin closest to the heart of our solar system, the sun. Rather -- the closest planet to the sun that I was able to image.
mars
Mars was captured using the telescope PROMPT-5. Well, every planet was captured using PROMPT-5. My groupmate, Christina Hollyday placed this observation. See the table below for information regarding exposure numbers, filters, and times.
Exposure # | Filter | Time (sec) |
10 | OIII | 0.6 |
10 | Halpha | 0.3 |
10 | U | 1.2 |
We chose to interleave our filters, meaning that the telescope cycled through each of our three filters in a row over and over. This ensures we will have accurate data even if part of our observation is separated or delayed by time or date.
Our first step for image processing is alignment. All of our planets are too small in our images to use feature-based AKAZE alignment. Instead, we must align our images based on the center of the featured planet. We had to go through every single exposure, clicking as close as possible to the center of the planet using the centroiding tool in Afterglow. We chose to enable source markers, centroid clicks, and planetary centroiding. This was a little bit of a tedious process! It was fairly easy for the Mars data as we only had 30 exposures to click through compared to the 90 exposures for Uranus.
I then compiled these stacks by filter, grouped these stacks together, applied color by making Halpha = red, OIII = green, and U = blue. I originally balanced these colors by means of percentile color balance mode: specifically, I used the midtone stretch mode with a default midtone level of 97.5 and saturation at 100.
Isn't Mars pretty?
Here's the image again, just a little smaller compared to an image of Mars from Stellarium at the same time our data was collected.
It's difficult to make out any detail in our image since these photos are blurred through Earth's atmosphere. Our color balancing method contributes to this as well -- percentile based color balancing only works when the brightest part of the image is white or close to white. As we can see from Stellarium, Mars is not predominantly white and thus the colors are not a completely accurate representation. The planet appears more exposed and white than it actually is.
To combat this I went in and manually edited the colors using histogram fitting but it didn't make much of a noticeable difference.
Fun fact:
Mars's red coloring comes from its iron-rich surface, which oxidizes and causes the red coloring we all know and love.
Next on the list, the big, the beautiful, the powerful "God of sky and thunder",
jupiter
Jupiter data was obtained from my groupmate, Glenn Lassiter.
Here's the observation information:
Exposure # | Filter | Time (sec) |
10 | OIII | 1 |
10 | Halpha | 1 |
10 | U | 1.5 |
The image processing process was very similar to Mars, I aligned my images one by one, clicking through each of the 30 exposures using planetary centroiding and then stacked them by filter. Percentile color balancing works pretty well for Jupiter because the brightest parts of it are in fact white.
The only part of the process that was different was that after creating my big beautiful Jupiter image I also wanted to explore/capture its moons. To do so, I changed my display settings from bright target to default, showing the moons at the expense of overexposing the planet.
Using Stellarium, I set the time to the Julian date of my observation to determine which moon was what. Above I've labelled these moons. Io, Europa, and Ganymede are the three moons that were present in my image.
An image like the one above is not possible without the means of photoshop as you can only choose to focus on either Jupiter OR its moons. If you choose to focus on Jupiter (bright target), the moons are eliminated from the image due to the sheer brightness of the planet. As seen in my second Jupiter image, when we choose to focus on the moons we heavily overexpose the planet, relinquishing any details or colors. I chose to photoshop my image for aesthetic purposes, plus, it just looks cool, wouldn't you agree?
Let's take a quick look at the details of Jupiter.
While the Stellarium view of Jupiter is obviously much more detailed than my image, I think it's still super cool to compare the two. I was able to capture the different colors of the large different stripes on Jupiter.
The colors of Jupiter are thought to be caused by ice. The yellow bands are specifically thought to be caused by ammonia ice, the brown are ammonia hydrosulfide ice, and the white is water ice.
Next up on the list,
Uranus
I placed the observation for Uranus, so this is all my own data.
Here's the observation information:
Exposure # | Filter | Time (sec) |
30 | B | 2.5 |
30 | V | 1 |
30 | R | 1 |
Initial image processing was the same as the previous two planets except for the fact that I had to click through 90 individual exposures for alignment, not 30. We are also using different filters, we opted to use B, V, and R instead of U, OIII, and Halpha. I stacked the images according to filter.
Uranus and Neptune are special when it comes to color balancing because we are able to have enough background stars in our image that we can photometrically balance them instead of percentile balancing. Why does this matter? It means that we can achieve "natural" or "true" colors for these planets.
In order to do so we must apply a world coordinate system (WCS) so Afterglow can determine and identify background star values as a calibration tool for our planet in the foreground. To do this, first reset your view in display settings to the default preset. The red (R) stack often has the most visible background stars so this is the easiest for WCS to be applied. To add WCS we go to the WCS calibration tab, select the red stack, and set the mode to platesolve. Once the job is submitted and (hopefully) comes back successful all we have to do is copy this WCS over to the green and blue stacks and then our whole group image will have coordinates applied.
As far as the photometric color balancing goes, underneath display settings I selected histogram fitting and then photometric color calibration. We must measure the zero points for each filter stack we have, however Afterglow makes this easy and does the work for us just at the push of a button. I calibrated my colors according to the blue filter because this is the filter that is the brightest for Uranus.
What we're left with is the true color of Uranus:
In photoshop I blew up my image and used a tool to measure the RGB Hex Code for the color: DEFFE8. The image on the right is a square of this color just to better represent it. I'd almost define this as a light mint color, it wasn't what I was expecting but it's super interesting regardless. I was expecting more of a blue heavy color, not green.
Uranus's blue/green color comes from its methane-rich atmosphere which absorbs red and infrared, resulting in a blue hue.
Similar to Jupiter, I was able to capture Uranus's moons by messing around with my display settings, changing from bright target to default preset.
I was able to capture and identify four of Uranus's moons, Titania, Ariel, Umbriel, and Oberon. I used Stellarium to identify these moons.
Last but certainly not least,
Neptune
Neptune data was obtained by my groupmate, Margaret Wright.
Here's the observation information:
Exposure # | Filter | Time (sec) |
10 | B | 15 |
10 | V | 7.5 |
10 | R | 7.5 |
Juuuust like all the past observations I aligned each exposure individually via planetary centroiding and stacked according to filter. I applied WCS to my image and used histogram fitting/photometric color balancing to bring out the true color of Neptune. The blue filter was chosen again as the calibration filter because the blue filter is the brightest for our observation.
In the same manner as Uranus, here's the actual color of Neptune! The RGB Hex Code is CBFFF9. It's a really pretty eggshell blue. This is about what I was expecting, however, I was under the impression that I would be seeing a darker blue color.
Neptune's blue color, like Uranus, is also a result of a methane-rich atmosphere. However, Neptune appears more blue than Uranus as Uranus has more of a haze built up in its atmosphere which dilutes the color.
As far as the moons go, I used the same process as the previous planets.
Here's what I was able to label:
I'll be completely transparent, I'm not super confident that this is a correct label. The view of Neptune from Stellarium showed many more moons than were actually visible in my image. Blurring at such these large scales may be at fault plus the overexposure from the planet may have washed these closer moons away. I chose to label this moon as Titan as it is Neptune's largest moon and is most likely to show in our imaging of the planet. Titan's location on Stellarium is also accurate to the moon I labeled.
reflection
I'm proud of the work I was able to accomplish even though I wasn't able to image all of the planets in our solar system. I learned a lot about color balancing, WCS, using Stellarium as a tool, and more. Hopefully some time in the future I can revisit this project and attempt to image some more planets that were not visible this time around. For example, I wish I was able to image Saturn as it's my favorite planet.
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