Since its inception as an educational project for understanding how the Sol’Ex works, JSol’Ex has grown into a powerful tool for processing and analyzing images captured with the Sol’Ex. However, it became very popular over time and started to be used outside the sole Sol’Ex community. In particular, it is now a tool of choice for many spectroheliographs owners.

I have always been keen on providing a user-friendly interface while keeping a good innovation pace. JSol’Ex was the first SHG software to offer:

All integrated into a single, easy to use, cross-platform application: no need for Gimp, ImPPG or Autostakkert! (but you can use them if you want to!).

For this new release, I wondered if I should change the name so that it better matches the new scope of the project, but eventually decided to keep it as it is, because it is already well known in the community and that changing it also implies significant amount of time spent on this that wouldn’t go into the new features.

This version introduces a new tool to measure distances! This feature was suggested by Minh Nguyen from MLAstro, after seeing one of my images in Calcium H, which showed a very long filament:

This tool lets you click on waypoints to follow a path and make measurements on the disk, in which case the distances take the curvature into account, or outside the disk, for example to measure the size of prominences, in which case the distances are linear.

The measured distances are always an approximation, because it’s basically impossible to know at what height a particular feature is located, but it gives a good rough estimate.

Last but not least, this version significantly improves the scripting engine, aka ImageMath. While this feature is for more advanced users, it is an extremely powerful tool which lets you generate custom images, automatically stack images, create animations, etc.

In this version, the scripting engine has been rewritten to make it more enjoyable to use. It adds:

As well as new functions. Let’s take a deeper look.

I would like to thank all the users who have contributed to this release by reporting bugs, suggesting features, and testing the software. In particular, I would like to recognize the following people:

On March 29, 2025, we were lucky to get a partial solar eclipse visible in France, with a maximum of about 25%. I wanted to do what was a first for me, capturing the event, so I used a TS-Optics 80mm refractor with a 560mm focal length, equipped with an MLAstro SHG 700 spectroheliograph. The Astro Club Challandais was organizing a group observation this morning, but my initial decision was not to attend. Instead, I opted to limit the risks by performing this somewhat complex setup at home, in familiar territory. Unlike the SUNSCAN, using a spectroheliograph like the SHG 700 requires more equipment: a telescope, a mount (AZ-EQ6), and in my case, a mini PC for data acquisition (running Windows) along with a laptop for remote connection to the PC.

I have conducted observations away from home before, but from experience, setting everything up—including WiFi, polar alignment, etc.—can be a bit too risky for an event like this. So, all week, I anxiously monitored the weather. Yesterday, the forecast looked grim, with thick clouds and rain. However, the gods of astronomy were merciful, blessing us with a beautiful day. The sky wasn’t entirely clear, but it was good enough for observations.

First of all, I had a specific observation protocol in mind. As you may know, a spectroheliograph doesn’t directly produce an image—it requires software to process video scans of the Sun. In the case of the Sunscan, the software is built into the device, but for a Sol’Ex-type setup, an independent software handles this task. You are probably familiar with INTI, but I have my own software: JSol’Ex.

The advantage of developing my own software is that I was able to anticipate potential issues. One major challenge with an eclipse is that the software must "recognize" the Sun’s outline, which won’t always be perfectly round—in fact, it could be quite elliptical. The software corrects the image by detecting the edges, but when the Moon moves in front, the sampling points become completely incorrect, sometimes detecting the lunar limb instead of the Sun’s!

My strategy was to start early enough to adjust settings for minimal camera tilt and, more importantly, to ensure an X/Y ratio of 1.0. With these reference scans, I could then force all subsequent scans to use the same parameters. So, I began my first scans under a beautifully clear sky! After some adjustments, I was ready: a single scan, and we were good to go!

At the same time, I activated JSol’Ex’s integrated web server and set up a tunnel so my friends could watch my observations live! I planned to perform a scan every two minutes using a Python script in SharpCap, automating the recording, scan start, stop, and rewind. JSol’Ex’s "continuous" mode processed scans in real time. Everything was going smoothly…​ until panic struck—clouds!

For the past three hours, the sky had been perfectly clear. Yet, just ten minutes before the eclipse began, clouds started rolling in. What bad luck! Fortunately, by spacing out the scans, I managed to capture many of them in cloud-free moments.

The eclipse began, and the first scans featuring the Moon appeared. It worked! Forcing the X/Y ratio was effective!

As the scans piled up, I encountered a new problem. While locking the X/Y ratio helped, the software still needed to calculate an ellipse to determine the Sun’s center for cropping. But things started going wrong—the software was miscalculating everything. I had anticipated this, and I already had a workaround in mind, but the necessary code wasn’t deployed on my mini PC. So, I didn’t worry too much and simply shared the raw images, which were perfectly round—because, as you recall, I had already adjusted my X/Y ratio to 1.0!

I continued scanning, though my setup wasn’t perfectly precise. My polar alignment wasn’t flawless, and I had no millimeter-accurate return-to-start positioning. As a result, I had to manually realign between each scan. While this wasn’t a major issue, it did create some intriguing scans. For those familiar with Sol’Ex, seeing "gaps" in the spectrum due to the Moon’s presence was quite unusual, making centering more difficult.

Time passed, scans continued, and finally, we reached the maximum eclipse phase!

At one point, I wondered whether we could see lunar relief in the images. However, given the jagged edges typical of SHG imaging, it was hard to say for sure, but, I think some of the details visible below are actual surface details.

By the end of the eclipse, I had 80 SER files, taken between 9:37 AM and 1:43 PM, totaling nearly 175 GB of data! It was time to transfer everything to my desktop PC to create an animation. This also gave me a chance to test whether my earlier workarounds for ellipse detection would function as expected. I ran batch processing, and boom—within minutes, I had this animation:

And here’s the continuum version which was weirdly compressed by Youtube:

This was just a first draft, using a beta version of my software. A few hours later I released a new version of the animation which is visible below:

In the end, the experiment was a success! I also took this opportunity to improve my software, which will benefit everyone. If you have eclipse scans, don’t discard them! Soon, you’ll be able to process them too.

The big question now is: Could this be done during a total solar eclipse, such as next year’s in Spain? Well, I feel lucky that this one was only 25% partial. Managing ellipse detection and mount realignment between scans is already quite tricky. During a total eclipse, there wouldn’t even be a reference point!

Unless one has flawless alignment, a mount capable of returning to position perfectly, and a steady scanning speed, this would be a real challenge. Honestly, it’s beyond my current expertise—it would require a lot more work.

P.S: For french speaking readers in west of France (or simply if you are nearby at that date), we organize the Rencontres Solaires de Vendée on June 7, where we can discuss this topic!

As you can see, I had been working with MLAstro for quite some time already, but I didn’t own the instrument. This has recently been "fixed" and I’m now a happy user of the SHG 700!

I must say that Minh’s design is fairly impressive, it’s a truly qualitative instrument. The aluminum housing makes it extremely robust, without any flexion, and it comes pre-collimated. In addition, the micro-focusers, which are used for the collimator lens, for the camera objective and for the wavelength selection wheel, are extremely pleasant to use: anyone who has struggled with the collimation of the Sol’Ex will immediately feel the magic.

Being a regular user of the Sol’Ex, I immediately felt comfortable with the SHG 700: it only took me a few minutes to setup and get my first images! Fine tuning the focus is a breeze with the microfocusers, it’s really fantastic to use.

My first images were showcased by MLAStro, but here are a few:

While the above images were fairly easy to produce, I was puzzled because I didn’t manage to get any decent image in Helium D3. This was surprising, because the sensitivity of the SHG700 is higher, especially because there’s no need for a ND filter or a an ERF, so it was curious that the only helium image I was able to produce was this:

To understand the problem was that, it is important to mention that unlike Minh, I was using JSol’Ex one-click, fully automated processing, a feature which was introduced a while ago (June 2024) and worked extremely well for both Sol’Ex and Sunscan files (N.B: the Sunscan app introduced the same feature a few days ago).

This feature only works if we can properly compute the dispersion of the spectrum, which is measured in Angstrom/pixel. In order to compute this, we need to know the specifications of the spectroheliograph, such as the grating density, the focal length of the collimator and objective lenses, the total angle as well as the pixel size of the camera. Once we know all this, we can determine how many pixels separate the reference line that we use, for example the Sodium D2 line, from the Helium D3 line. To illustrate this, let’s say that we have a dispersion of 0.1Å/px. The Helium line is to be found at 5875.62Å, when the reference line, the Sodium D2 line, is detected at 5889.95Å. Therefore, the Helium line can be found 14.33Å away from the D2 line, which means 14.33/0.1 = 143.3 pixels away.

Using both Sol’Ex and Sunscan, I had great experience at extracting this line automatically, so it was to say the least curious that it wouldn’t work with the SHG 700.

So I contacted Minh, and after eliminating obvious possible candidates, like weak signal or incorrect exposition or gain, I decided to go the "old way" and searched for the helium line manually. It was with great surprise that I discovered that when JSol’Ex told me that the line should be 124.9, I was measuring something closer to 116 pixels! I brought this to Minh, and we identified 3 possible causes for this:

It was also possible, but unlikely, that a combination of 2 and 3 would happen. The first thing I’ve done is double checking my formula to compute the dispersion in JSol’Ex. I was doubtful that it could be wrong, given that it was used with success on different SHGs. In addition, it gave exactly the same result as the Ken Harrison' SimSpec SHG spreadsheet.

So we moved to the 2d option: the SHG 700 was advertised with a focal length of 75mm. However, the pixel shift I was manually measuring was closer to 70mm. I brought this again to Minh, who contacted the supplier of the lens, and here’s what he told me:

So I changed the focal length to 72mm and got this image instead:

and a stack of 5 images processed entirely in JSol’Ex:

That’s quite a difference! So it appeared that the software was correct, and that it allowed identifying a problem in the spectrograph specifications, because a spectral line wasn’t found where it should have been! While going from 75mm to 72mm won’t make much of a difference, the fact of not using the right numbers makes a huge difference in JSol’Ex: computations are all off, which includes the pixel shifts like in this exercise, but also the measured redshifts. In addition, this would make it impossible to perform more complicated tasks like finding the ionized Fe lines when imaging the corona E. The image is stil less contrasted than it should be, which may indicate that the computation is slightly off, or it’s just due to the weather conditions that day, I didn’t have the opportunity to retry.

Lastly, we can actually see fairly easily that the new focal length is a better fit, by using JSol’Ex "profile" tab. In that tab, we compare the profile of the spectrum that you captured with a reference spectrum from the BASS2000 database: this is also how the software automatically determines what spectral line is observed, by comparing the profiles together.

With a 75mm length and an H-alpha profile, here’s what we got:

You can see that while the H-alpha profile is found, as soon as we move towards the wings, there are slight shifts between the local minimas. When we switch to a 72mm length, these are perfectly aligned:

The SHG 700 is a fairly impressive instrument: it’s robust, it’s a pleasure to use with its microfocusers, and Minh is always super responsive and very patient. Its use doesn’t come without drawbacks, though. It’s weight, for example, restricts it to refractors which have a good focuser. The dimension of the sun is also smaller than with the Sol’Ex at equivalent focal length (see this post for an explanation). However, it produces stunning images, sometimes rivalizing these produced with an etalon.

While testing it, I faced this problem that the helium line images were significantly worse than with the Sol’Ex, which didn’t quite make sense. After investigation, it turned out we had highlighted a difference in the specifications, a lens had been changed from 75mm to 72mm by the supplier, without letting MLAstro know. That’s a pity, but, in the end, the problem is very easy to fix in JSol’Ex. Be sure to upgrade to JSol’Ex 2.11.2 which includes a fix to update the focal length.

First of all, a bit of vocabulary. An active region is a region of the Sun atmosphere where special activity occurs, such as flares or coronal mass ejections. They don’t have to be associated with sunspots, but in general, they are. In JSol’Ex, we’re essentially detecting sunspots, and the terminology "active regions" essentially comes from the fact that we can use the https://www.swpc.noaa.gov/NOAA database] to label these active regions.

An instrument like Christian Buil’s Sol’Ex, called a spectroheliograph (or SHG in short) doesn’t offer any kind of "live view" like typical solar instruments like Coronado or Lunt instruments. Instead, what we get is a video file, where each frames consists of a "slice" of the sun, observed as a portion of the light spectrum:

The video above is an excerpt from a so-called "scan": the principle is to have a slice of the sun passing through a slit, and a grating is used to spread the light into a spectrum. Here, we are observing a curved dark line, which is the H-alpha line, and the "wobbling" we see around that line is an illustration of the Doppler effect. The idea of software like Valérie Desnoux’s INTI and JSol’Ex is to extract pixels from the studied line (here H-alpha) in order to reconstruct an image of the sun.

However, as you can see in that animation, there’s a lot more information available in each frame. While we are mostly interested in the central line (here H-alpha), it’s also interesting to look "above" or "below" the line, which is often referred to "pixel shifting", in which case we’re not studying H-alpha, but a different wavelength: that’s one of the strenghts of Sol’Ex, which makes it possible to do "science" at home!

In particular, this video shows a couple interesting features:

This video is actually an excerpt from one of the many captures I’ve done with Sol’Ex, and I captured it during an eruption, on May 5th, 2024. What you are seeing here is the massive AR3664 region which was suject to multiple X-flares and resulted in beautiful auroras on Earth!

I’ve always considered that it would be a cool feature to be able to detect these lines automatically in JSol’Ex, and provide an overlay of the detected sunspots. Here we go, it is finally implemented in JSol’Ex 2.9.0! If you select the "full processing mode" or that you check the "active regions" checkbox in a custom process, then JSol’Ex will automatically create an image of the sun with the detected active regions as an overlay:

Unfortunately that day I didn’t capture a full disk, but you can see that JSol’Ex annotated the disk with the detected active regions, but it also added the labels for these regions automatically.

Let’s take another example with an image captured in Calcium K on January 17, 2025:

You will notice 2 different colors for labels:

Sometimes, you will see like in the image above regions which are not detected, and others which are detected but not in the NOAA database. The reason why not all of them are detected is that I had to choose "reasonable" detection thresholds, which work for most use cases. I plan to improve the algorithm over time to make it more robust, based on your feedback.

The algorithm is based on a simple analysis of each frame. If you open your SER file in JSol’Ex video analyzer, you will see something similar to this:

On the top, you see the original frame, with the curved H-alpha line. On the bottom, you see the corrected frame, where the H-alpha line is straightened, and the active regions are highlighted in purple.

The algorithm is based on the following steps:

For each frame:

The reason to only keep candidates which have both average intensity and standard deviation below a threshold is because:

At the moment, I’m using the following thresholds (note that they may change in future releases, as I improve the accuracy):

Once we have the results for all frames, we aggregate active regions by collecting adjacent candidates.

Finally, we filter out regions which are too small, then perform clustering of regions which are close to each other.

The whole algorithm can be found here (note that it also includes redshift detection, which was discussed in a different blog post).

This algorithm proves to work relatively well in many different wavelengths (H-alpha, calcium, magnesium …​). However, there are sometimes false positives. This is for example the case when I’m scanning in H-beta, due to the long focal length of my telescope and astigmatism, and the fact that H-beta provides a lot of details.

In this case, the algorithm detects areas which are actually just noise:

Note that these are close to the north and south poles. I have also noticed that the algorithm tends to detect noise as active regions when we’re close to the limb, which is also why I’m currently filtering these out.

At this stage, I have chosen not to make the detection thresholds configurable, because I consider these internal implementation details, which may change in the future, and that I don’t want to expose to the user.

Once piece of work that we didn’t explain yet is how JSol’Ex puts labels around active regions. For this, we are using the NOAA Solar Region Summary database.

This provides us, at a particular date, the list of active regions with their positions on the solar disk. JSol’Ex will compare these with the detected regions, and put the labels in different colors based on whether they were detected or not.

However, the position of active regions will only be correct if:

The data from NOAA is cached in your local filesystem, so that we don’t have to download it every time you open a video file.

Despite only having released this a day ago, I already have received the same question multiple times: can JSol’Ex be used to annotate an existing image of the sun, that is to say, take a JPG or PNG image and annotate it?

If you have read carefully this blog post and that I explained things correctly, you will have understood that the answer is no: because my algorithm is based on the analysis of each frame, there’s no such information available in a single image.

I hope you will enjoy this new feature in JSol’Ex 2.9.0. This blog post is a tentative explanation of the algorithm, and I will be happy to answer any questions you may have about it. As always, feel free to contribute, JSol’Ex is open source!