datacarpentry / image-processing

Image Processing with Python
https://datacarpentry.org/image-processing
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Teaching lesson in disciplines where single-channel data is the norm #211

Open ivastar opened 1 year ago

ivastar commented 1 year ago

In astronomy scientists use single channel CCD images for their research. Color images are only created for publication purposes and for public outreach. There is a lot of very useful content in this lesson that can still be taught for single channel images but maybe some thinking needs to be done on how to present the material to learners who have rarely/never encountered multi-channel/color images in their work.

One suggestion that came from a discussion at CarpentryCon is to use separate images at different wavelengths as the different channels. Images need to be registered in order for this to work.

Are there other disciplines that use primarily single-channel data?

bobturneruk commented 1 year ago

Lots of optical microscopy (and I think also some satellite imaging). Often these are quite well registered (i.e. aligned across channels), but that's another consideration that I hadn't thought of.

Does including RGB as standard place too much of a burden on learners only interested in single channel data, I wonder? And related, can learners go on to apply knowledge of RGB to deal with different types of multi channel data e.g. two infra-red bands? Maybe some more "information boxes" in the initial episodes would be sufficiently helpful?

K-Meech commented 1 year ago

Just to add that this is also common with scientists who mostly work with electron microscopy, or X-ray microscopy data. There are rarely RGB images.

Some extra 'information boxes' are a good idea. It would be nice to make it clearer how these principles of working with RGB can be extended to any multi-channel data (which is also common e.g. with multi-channel fluorescence microscopy images)

tobyhodges commented 5 months ago

@ivastar I was chatting with @tischi earlier this week and the prospect was raised of a hackathon-like event to try sketching out alternative versions, forked from this lesson and modified to use different central example datasets. We discussed the idea of one version using the kind of microscopy data mentioned by @K-Meech above (@tischi expects to know plenty of people who might contribute to that effort), and a second for the kind of astronomical data you mentioned above.

It sounded like there was some potential for such an event to be hosted in Heidelberg. Does this sound interesting to you?

mkcor commented 5 months ago

It sounded like there was some potential for such an event to be hosted in Heidelberg. Does this sound interesting to you?

If I may chime in, I don't live very far from Heidelberg. If you don't have a full team of instructors/helpers yet, I could join perhaps... depending on when you schedule the event (e.g., I'm not available in March).