It installs the complete software and creates a starter on the user's desktop.
Program execution is most efficient if the image data and all intermediate results can be kept in memory. After stacking is completed, the stacked image can be postprocessed (sharpened) either in a final step of the stacking workflow, or in a separate postprocessing job.Finally, all stacked patches are blended into a global image, using the background image in places without alignment points.Using those shifts, the alignment point patches of all contributing frames are stacked into a single average image patch.For all frames, local shifts are computed at all alignment points.
Note that this list can be different for different points.
(Alternatively, the user can select the patch manually as well.) On the best frame, a rectangular patch with the most pronounced structure in x and y is identified automatically.First, all frames are ranked by their overall image quality.The following algorithmic steps are performed: Input to the program can be either video files or directories containing still images. Starting with version 0.8.0, PSS can be used either in GUI mode or from the command line, e.g. The software has been tested successfully on Windows, various Linux distributions, and macOS. PSS is platform-independent and can be used where Python 3 is available. A modern graphical user interface (implemented using the QT5 toolkit) and good usability were high priorities in designing the software. The program uses array operations (OpenCV, numpy) wherever possible to speed up execution. Results obtained in many tests show at least the same image quality as with the established software AutoStakkert!3.
The program is mainly targeted at extended objects (moon, sun), but it works as well for planets. Produce a sharp image of a planetary system object (moon, sun, planets) from many seeing-affected frames using the "lucky imaging" technique.