planetary-system-stacker 0.8.32~git20221019.66d7558-1 source package in Ubuntu
Changelog
planetary-system-stacker (0.8.32~git20221019.66d7558-1) unstable; urgency=medium * New upstream release. -- Thorsten Alteholz <email address hidden> Wed, 14 Dec 2022 23:35:45 +0000
Upload details
- Uploaded by:
- Debian Astronomy Maintainers
- Uploaded to:
- Sid
- Original maintainer:
- Debian Astronomy Maintainers
- Architectures:
- all
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Lunar | release | universe | misc |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
planetary-system-stacker_0.8.32~git20221019.66d7558-1.dsc | 2.4 KiB | 25599cb54f1b69a6a97a499e824368ac8d75338491b8326cbf2058775b61ee5d |
planetary-system-stacker_0.8.32~git20221019.66d7558.orig.tar.xz | 28.8 MiB | 3f9fb0c98200fb6d07f51645aa7a7e4778b3112de3fd4c8a45066fe3dec22e6a |
planetary-system-stacker_0.8.32~git20221019.66d7558-1.debian.tar.xz | 2.5 KiB | 017ce6aaf3c2c30eecaf0298f7c0a194914929350a47c625feed11ed9d95f9aa |
Available diffs
No changes file available.
Binary packages built by this source
- planetary-system-stacker: 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.