Isis3: Anaglyph generation

[adakite]

I strongly think that offering an anaglyph generation in ISIS would be great. This is something useful for science, outreach and also when looking at the best results after bundle adjustment with a very efficient way of visualising the alignement of images and the resulting parallax.

Meanwhile, maybe there is out there some tools able to do that (besides SOCET SET) accounting the for spice/sensor models.

Thanks

[jlaura]

@adakite If you could use the feature request template for the submitted issue that would be appreciated! What does the interface for this look like? What types of data does this support? What are the input/output formats? How would you want to use a tool like this, etc.

I have copied the template, that is displayed when opening a new issue, below for your convenience. You should be able to edit your issue and update the contents. If not, please reply and let us know so that we can assist you.

**Description**  
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**Example**  
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[adakite]

Description
Request for a new tool in ISIS, able to generate anaglyph.

Motivations
I strongly think that offering an anaglyph generation in ISIS would be great. This is something useful for science, outreach and also when looking at the best results after bundle adjustment with a very efficient way of visualising the alignement of images and the resulting parallax.

Meanwhile, maybe there is out there some tools able to do that (besides SOCET SET) accounting the for spice/sensor models.

Example
anaglyph from1=isis_imgage1.cub from2=isis_imgage2.cub to=my_anaglyph.png format=PNG

from1 being left image, from2 being right image and isis_imgage*.cub being typical mapped/nonmapped Spiced ISiS3 cube images and the output should be in std, such as TIF or PNG as an option. Scalebar may be added optionally as well.

Thanks

[jlaura]

@audiefen Wonderful presentation at the 2019 Data User's Workshop!

I wonder if the code that you are using to build anaglyphs (using ISIS) might be made available somewhere? I think your use case is a great example of code that uses ISIS to solve a pretty specific problem. Thanks!

[audiefen]

Thanks @jlaura!

The code is not available at this time and is still in development. I am interested in making it available though. I would love it if others found it helpful in some way, but I would also welcome any feedback on the code itself (this was my first endeavor with python), as well as any advice on how to improve/make more efficient the image registration approach.

I need to run it by mission PI before making it available. I'll get back to you. Thanks!

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