StarStaX is a fast multi-platform image stacking and blending software, which allows to merge a series of photos into a single image using different blending modes. It is developed primarily for Star Trail Photography where the relative motion of the stars in consecutive images creates structures looking like star trails. Besides star trails, it can be of great use in more general image blending tasks, such as light painting, noise reduction, or synthetic exposure enlargement.
StarStaX has advanced features such as interactive gap-filling and can create an image sequence of the blending process which can easily be converted into great looking time-lapse videos. Check out the StarStaX Flickr Group for some great photos created using StarStaX!
StarStaX is available as a download for Mac OS X and Windows. It is free to download and free to use for any purpose, including commercial projects.
- Blending/stacking modes: Lighten, Darken, Average, Addition, Subtraction, Multiplication
- Interactive gap filling mode to automatically close small gaps in star trails (see the StarStaX tutorial)
- Comet mode blending to create comet-like star trails
- Supports a multitude of image formats (JPG, TIFF up to 16-bit/channel, PNG, etc.), Raw images cannot (yet) be developed using StarStaX – there are many better tools for that. For Raw images, use your favorite Raw converter, make your adjustments and export the images as TIFF.
- Cumulative mode: A stacked image can be saved after each frame is processed (to create a cumulative stacking video)
- Averaging and subtraction of dark frames to remove hot pixels and noise
- Smooth zoom, 100% view, different view interpolation modes (anti-aliasing)
- GPU support for fast navigation within images
- Multi-touch / mouse wheel support for scrolling
- Multi-CPU / multi-core and SSE optimized for processing speed
- Multi-language (currently: English, German, French, Italian and Spanish)
- StarStaX is fully 64-bit enabled on all platforms
Mac OS X version
StarStaX requires Mac OS X 10.7 Lion or higher and a 64-bit capable Intel processor (Intel Core 2 Duo or better). To find out if your Intel Mac has a 64-bit CPU, please refer to: http://support.apple.com/kb/HT3696
StarStaX requires Windows 7 or higher.
Download and Installation
StarStaX is available as a download for Mac OS X and Windows. It is free to download and free to use for any purpose, including commercial projects. Installation instructions are given below.
Mac OS X 10.7 (OS X Lion) – 10.15 (OS X Catalina)
Note to users of Mac OS X 10.15 Catalina:
StarStaX 0.8 with better support for Catalina will be released in Feb/Mar 2020. StarStaX 0.71 works well on Catalina but you might experience some display artifacts. For testing, a beta version of StarStaX 0.81 is available for download.
Feedback is highly appreciated via eMail to email@example.com.
To install StarStaX, please download and mount the disk image and drag StarStaX to your Applications folder. Double-click on the StarStaX application to run StarStaX.
In case of problems when opening StarStaX, please review the FAQs.
Windows (32-bit and 64-bit)
StarStaX (32-bit) is available as a .zip file from here:
To install StarStaX, extract the .zip archive and double-click on “StarStaX.exe” in the folder StarStaX-0.71. There is no installer. You can manually copy the StarStaX folder to any folder you like and create a link to StarStaX.exe, e.g. on the desktop or in the program menu. To uninstall just remove the StarStaX folder from your harddisk.
You may need to install the Microsoft Visual C++ Redistributable Package to install the necessary run-time components. To do so run vcredist_x64.exe and follow the installer.
See the “readme_install.txt” file in the .zip archive.
Many thanks to
- Christian Enzweiler for design and graphics work
- Alfonso Pereira Castro for the Spanish translation of StarStaX
- Rubeluta Valentin for the French translation of StarStaX
- Paolo Cosentini for the Italian translation of StarStaX
- All the StarStaX users for lots of feedback and suggestions
- The girls and guys behind the amazing Qt framework