How to Install and Uninstall planetary-system-stacker Package on Kali Linux

Last updated: December 23,2024

1. Install "planetary-system-stacker" package

Please follow the step by step instructions below to install planetary-system-stacker on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                planetary-system-stacker
            
                    
    
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2. Uninstall "planetary-system-stacker" package

This guide covers the steps necessary to uninstall planetary-system-stacker on Kali Linux:


    
        
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                sudo apt remove
            
                        
                planetary-system-stacker
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the planetary-system-stacker package on Kali Linux

Package: planetary-system-stacker
Version: 0.8.32~git20221019.66d7558-2
Installed-Size: 1024
Maintainer: Debian Astronomy Team
Architecture: all
Depends: python3-astropy, python3-matplotlib, python3-numpy, python3-psutil, python3-pyqt5, python3-scipy, python3-skimage, python3:any, python3-opencv
Size: 149488
SHA256: 525bc9bc24cc214b2cc156f3ea6d4e13e2b2f0e0f80e5ffbb42cd4389b818163
SHA1: 92d9227b813243c5a4f20112d8477d51665036b2
MD5sum: 06dc56ae8c532c17889f9ca548e37483
Description: create a sharp image of a planetary system object (moon, sun, planets)
This package contrains software to produce a sharp image of a planetary
system object (moon, sun, planets) from many seeing-affected frames using
the "lucky imaging" technique._
.
The program is mainly targeted at extended objects (moon, sun), but it
works as well for planets. Results obtained in many tests show at least
the same image quality as with the established software AutoStakkert!3.
.
Input to the program can be either video files or directories containing
still images. The following algorithmic steps are performed:
.
* First, all frames are ranked by their overall image quality.
* On the best frame, a rectangular patch with the most pronounced structure
in x and y is identified automatically. (Alternatively, the user can
select the patch manually as well.)
* Using this patch, all frames are aligned globally with each other.
* A mean image is computed by averaging the best frames.
* An alignment point mesh covering the object is constructed automatically.
Points, where the image is too dim, or has too little contrast or structure,
are discarded. The user can modify the alignment points, or set them all
by hand as well.
* For each alignment point, all frames are ranked by their local contrast
in a surrounding image patch.
* The best frames up to a given number are selected for stacking.
Note that this list can be different for different points.
* For all frames, local shifts are computed at all alignment points.
* Using those shifts, the alignment point patches of all contributing
frames are stacked into a single average image patch.
* Finally, all stacked patches are blended into a global image, using the
background image in places without alignment points.
* 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.
Description-md5:
Homepage: https://github.com/Rolf-Hempel/PlanetarySystemStacker
Section: science
Priority: optional
Filename: pool/main/p/planetary-system-stacker/planetary-system-stacker_0.8.32~git20221019.66d7558-2_all.deb