PixInsight Forum (historical)
PixInsight => Tutorials and Processing Examples => Topic started by: oldwexi on 2013 May 18 16:34:10
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Hi!
I have produced two new video tutorials for PixInsight.
The titles are:
PixelMath
Basic Functions Part II
its a follow on to PixelMath Basic Functions Part I Video tutorial.
It shows simple Calibration with PixelMath,
simple stacking and removal of Satellite trails, mixing of H-Alpha into RGB using PixelMath.
Using PixelMath to correct starmasks and using 2 masks on one image by the use
of PixelMath and a normal mask.
It lasts 22 minutes (Size of Video 82MB).
Hope you will find this video useful.
Here the link to the english version of the
PixelMath Basic Functions Part II video:
http://dl.dropbox.com/u/57910417/Video08_PixelMath_IIa_english.wmv (http://dl.dropbox.com/u/57910417/Video08_PixelMath_IIa_english.wmv)
The title for the second video about PixelMath
is:
PixelMath for
Analyses, Masks and Midtonetransfer
In this video
first you will see how to use PixelMath to analyse
Functions and calculation operations by making them visible graphically as a curve.
Second you will see the use of an additional temporary masks within
PixelMath
and third you will see multiple masked stretching of images
using Midtonetransfer with masks in PixelMath.
It lasts 32 minutes. (83MB)
Here the link to the english version of the
PixelMath
Analyses, Masks and Midtonetransfer video:
http://dl.dropbox.com/u/57910417/Video09_PixelMath_IIb_english.wmv (http://dl.dropbox.com/u/57910417/Video09_PixelMath_IIb_english.wmv)
If you want to test the processes of this video
with your own data without typing in everything you can
download all the used processes from my homepage:
http://www.werbeagentur.org/oldwexi/Daten/PixelMath_II__Processes.zip
After unzip in a directory, you drag and drop this single xpsm-file from your
directory on your PI-workspace and have ALL the processes used
in the video as macros available.
If you understand German and want to use these videos and my other
PixInsight videos in german language,
they are all selectable here on my homepage:
http://www.werbeagentur.org/oldwexi/PixInsight/PixInsight.html (http://www.werbeagentur.org/oldwexi/PixInsight/PixInsight.html)
Another collection of German videos and tutorials you can find
on the homepage of
our Austrian PixInsight Jedi Herbert Walter
http://www.skypixels.at/pixinsight_tutorials.html (http://www.skypixels.at/pixinsight_tutorials.html)
Have Fun with PixelMath in PixInsight
Aloha
Gerald
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Thanks Gerald,
Always appreciate your good work.
Mark
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Very interesting, Gerald. With these videos, you contribute a less common approach to using pixinsight, that provides a lot of insight. Thank you for taking the time.
Ignacio
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Very intriguing Gerald. It will take some time to absorb the content in these two videos. I have one question concerning the mask that isolates just one corner of the image. This seems a little like a hand painted mask in Photoshop. What are your thoughts on how this fits in with the overall PixInsight philosophy?
Keep up the good work. I look forward to the next video.
Geoff
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Hi Geoff!
The cornermask is, a you mentioned, an offense against the PI philosophy. I fully agree. And i dont do it myself.
But for those who still think they need to move to PS for this kind of postprocessing they have one reason
less to move the data into the painting Programm and loosing data because of conversion...
My intention is to show that there s no need at all to do the "final tweaking" or "any "tweaking" in PS.
The move to the correct treatment and clean philosophy of handling data
will come more easy if PS is more and more visible obsolete.
Aloha
Gerald
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Good points Gerald. Thanks for clarifying.
Geoff
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The cornermask is, a you mentioned, an offense against the PI philosophy.
It depends on how and why you apply it. If by "PI philosophy" you mean my philosophy, then here it is. If you:
- Analyze the data to find and outline the problem,
- Understand the problem and its causes (for example, an ampglow artifact or a light leakage issue in this case),
- Design a suitable solution to the problem (a local mask in this case),
- Evaluate the side effects and the risks of your solution (decreased SNR on the masked area in this case, and the risk of introducing a nonuniform illumination artifact),
- Make an informed decision as to whether the solution of the problem is worth the side effects and risks,
- Apply the solution strictly to solve the problem, preferably in a purely algorithmic way,
- Evaluate the result of the applied solution and its side effects,
then what you are doing is astrophotography: Turning data into information to communicate something from nature. However, if you do one or more of the following:
- Apply arbitrary manual retouching techniques without documentary criteria (example: create a layer mask, paint it with a brush by hand, then sharpen where you want because it looks nicer that way),
- Remove objects or image structures selectively, without documentary criteria (for example, removing all the stars in a wide-field image can be a nice way of revealing the true shape of a nebula, but removing a large blooming by cloning its adjacent pixels is like "inventing" that part of the image),
- Add artificial elements or artifacts "for aesthetic purposes" (example: artificial star spikes),
- Apply any process selectively without documentary criteria, i.e. without criteria based on a thorough analysis and understanding of the properties and nature of the data and of the objects represented (typically also for aesthetic reasons),
- Apply processes incorrectly, or without the necessary knowledge and common sense, (typically, trying to process an image beyond the reasonable limits imposed by the SNR of the data),
then what you are doing is, to a lesser or greater extent, painting. Downloading the image from the Internet to modify it, or painting it directly on a canvas, may be easier than acquiring it from the sky, and the results may be aesthetically better, too.
Astrophotography, as I understand it, is much more about the "how" and the "why" than about the results. When I look at an image, I need to be sure that I can trust what I am seeing. For this to happen, I need to know how the image has been processed and why. In essence, this is also the philosophy behind PixInsight, but everybody can use a tool as they want.
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Thank you Gerald for these new jewels in PI tutorials.
I Appreciate them very much.
Waiting for the next ;)
Bye Edoardo