Command-line software comprises programs that are run from a terminal window rather than from a GUI (graphical user interface). This is reminiscent of using DOS or CPM or mainframe operating systems before the days of Windows-like GUI operating systems. In fact, Linux and even Windows users still use the command-line interface to achieve very powerful results.
Location of the star-removal software:
https://github.com/code2k13/starreduction
For Linux a tar.gz file is downloaded:
starrem2k13_ubuntu_20.04.tar.gz
This file contains all of the components including the Linux binary
For Windows a .zip file is downloaded
starrem2k13_win.zip
This file contains a .exe file which installs the Windows binary and the other components.
The Linux and Windows command-line programs are used in almost identical ways. In each case a directory (folder) exists containing all of the required files.
In both operating systems the starry image is placed in the same folder. If it is given a short filename it will be simpler to use. Moreover, one should never use spaces in filenames in Linux. It is better practice to use an underscore rather than a space in a filename in any OS.
In Linux the executable file is called starrem2k13
In Windows it is called removestars.exe
In both Linux and Windows a terminal is launched inside the same folder as the executable and the starry image file (which in the case here we have called EastVeil.jpg).
The following line is typed or pasted into the terminal of Linux or Windows.
The two lines are similar but not identical. The difference arises because the start of the line begins with two characters which are required by a POSIX environment (Linux) or a Windows environment. The other difference is in the name of the executable: starrem2k13 in Linux and removestars.exe in Windows.
Command-line Linux
./starrem2k13 EastVeil.jpg starless.jpg
Command-line Windows
.\removestars.exe EastVeil.jpg starless.jpg
When enter is pressed after the command-line has been entered, the stars will be removed from the starry image and a starless image (in this case starless.jpg) will appear in the same folder. This is somewhat reminiscent of the use of the command-line version of Starnet++ but has less stringent requirements of the file having the stars removed.
Windows
Screenshot of the star removal software running at the command-line in Windows
Linux
Screenshot while the star removal software is running
Screenshot after the star removal software has completed the star removal
Notice that the starless image has now appeared in the folder
It should be noted that there seems to have been no work done on this open source project since 2023. For macOS there only seems to be a Unix executable for x86_64 but not for Apple silicon. Readers can try the macOS version if they have an appropriate machine but we shall look only at the Linux and Windows versions. Also the author of the software has apparently produced some sort of Python front end, but we shall only be considering the command-line implementations.
Initial testing indicates that the software works with 8 bit and 16 bit image files but not with 32 bit images.
There is an online demonstration version of the software that runs entirely in your browser and allows uploading a square image of up to 1024 x 1024 and downloading the starless image at a lower resolution. Uploading an oblong image will allow star removal but the starless image is distorted into a square image.
https://ashishware.com/static/star_removal/index.html
Screenshot of the browser in which the demonstration of the software removing stars from an uploaded image and producing a starless downloadable image.
This would not be useful for a workflow but is intended for a potential user to judge the efficacy of the software.
The AI model was trained on data created by a GAN (Generative Adversarial Network) which is a powerful deep learning model using two competing neural networks: a Generator and a Discriminator to create realistic, new data. This is a process called data Augmentation: Producing more training data for other AI models such as the star removal software.
We are introducing this star removal software here for a specific reason.
It is noticed that a large number of smart telescope users such as Seestar users are content to display and share the results of live stacking with little, if any processing. If attempts are made to enhance the images produced by the Seestar, brightening the nebula will result in a concomitant brightening of the stars which is an undesirable effect, bloating the stars and tending to saturate them, losing the star colours in the process.
On 27 August 2025 I published a blog article on 'Using AstroEdit on iOS to process Seestar images'. That software gives iOS users the ability to remove stars from their Seestar images, brighten up the nebulosity to an extent and then replace the stars in the image. The problem is that at the time of writing, AstroEdit is not available in a fully functional form for use on Android devices or Amazon Fire devices at all, both of which are also used for controlling Seestars and capturing deep sky images.
If data are downloaded from a Seestar onto a computer, all sorts of possibilities appear. It is possible to stack all of the individual sub-frames in software such as PixInsight or Siril and to completely process the images in those programs as well as others such a GraXpert, Gimp, and many others. However, we are considering here the case when a user is content to useLocation of the star-removal software: for example the high quality JPG that is produced of the stacked image by the Seestar but would like to be able to boost the nebulosity a little without burning out the stars.
In such as case, just Gimp and the starrem star removal software can achieve good results without the huge learning curves associated with more sophisticated software. Also these programs are open source and free to ‘own’ and use.
It is conventional wisdom that one does not use JPG images for processing because the image is saved in a lossy format in which some information is discarded. In high quality JPGs it is still possible to do a limited amount of processing but it is best to save the results in an uncompressed format such as a PNG or a TIF file. It is by taking advantage of this fact that Seestar users can improve their images that were saved as JPGs by the Seestar.
So for example, one could use the command-line star-removal software to accept a JPG and to output a PNG or TIF. For example:
In Linux
./starrem2k13 EastVeil.jpg starless.png
In Windows
.\removestars.exe EastVeil.jpg starless.png
Starry JPG on the left and starless PNG on the right
In Gimp is a simple matter from the starry and starless images to create a star image which can be added back to the enhanced nebulosity image with any required level of prominence.
The starless image is pasted as new layer onto the starry image with a Mode of Subtract or Difference (whichever gives the best result). The star image is flattened and pasted as a new layer back onto the starless image which may have been enhanced with Curves and/or Levels. The Mode would be Screen or Addition (whichever gives the best result). Then with focus on the pasted star layer, Curves are used to increase or decrease the prominence of the stars as required. The image is then flattened and exported as the final processed image.
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