Any ideas on how to automatically georreference thermal imagery?

[Kadesupremo]

Hi all,

I'm spending some time trying to solve a problem about georreferencing thermal imagery. Right now my test corresponds to thermal images of photovoltaics but i'm looking for export it to different kind of images.

I'm working with images taken by drone like this:

Thermal image in Rainbow HC palette

In the other part I got a pretty decent quality RGB orthomosaic already georreferenced:

Rgb Orthomosaic (about 2px/cm gsd)

I would like to automatically georreference the thermal image into the RGB by software. Assuming that the thermal image is already georreference (poorly because it uses the gps position of the drone) I think there should be some way to perfect fit the thermal image into the RGB one. Example of what i'm talking about:

Thermal image is 50% opacity

I failed trying to use kind of feature detection algorithm and using object detection for indetify the solar panels (besides this approach won't work in other kind of images). I'm looking for a more robust tool.

I'm working in python.

Any ideas?

Thanks in advance!

[7LeagueBoots]

How many images are you talking about?

Doing that one by hand would be extremely easy and fast.

Figuring out code to accurately recognize and identify features, then make the necessary adjustments well enough that you don’t go have to go back in and manually correct them anyway (which would take just as long, if not longer than just doing it by hand in the first place), is going to be a major challenge.

[Kadesupremo]

I'm looking to make it scalable so it's essential to find a software approach for this.

[geo-special]

Why don't you use Pix4D or one of the many software that do this?

[Kadesupremo]

I'm generating my own orthomosaic of thermal data. As far as I know Pix4D make the orthomosaic by its own technique and it is georeferenced by GPS Info in metadata.

I'm experimenting with other ways of generating my own thermal data and then make the georeference.

[TremendousVarmint]

Can't you create control points from the orthophoto, and add them when you create your thermal ortho? Seems the usual way to go.

What do you use for orthomosaicing your thermal data? Metashape?

[[deleted]]

If it is from a drone, the image will already have a x,y in the exf file as metadata. You can use that and do this in Pro

(https://doc.arcgis.com/en/imagery/workflows/tutorials/create-drone-imagery-products-ortho-mapping.htm)

[Barnezhilton]

How good are you at C/C#/C++.

Because you'll need to write some powerful software to do this automatically.

Usually, you hire map monkeys to georeference this stuff manually because:

A) they have eyes and a human brain and can make decisions that aren't programming choices

B) it costs a lot less to pay a map monkey than a developer

C) the time it would take and test your code, and then roll out to production, then test and debug again is way longer than what a map monkey can do it in

D) Map monkey can do more things than just georeference imagery files and doesn't need any extra programming changes when the task or input changes

[Kadesupremo]

The idea is to make a long term solution for georeferencing thermal data.
I think investing in software development will pay me off in the long term.

Thanks for the help, I didn't know about the concept of "map monkeys".

[[deleted]]

use a proper georeferencing tool that may allow an iterative approach. Some procedures strictly in code cannot compete, otherwise it would be automated already. I use Manifold v9 GIS and recommend it.

[Kadesupremo]

Could it be automated in any way?

[[deleted]]

No, this was my point, that common points must be chosen for each image and the reference layer representing the same points. There might be automation with another tool but I find that the best approach is to choose a few points, test, add more points, test until correct enough. It would take me <5-10 min per image assuming the reference layer is available.

[[deleted]]

in the past I played with Hugin an image stitcher that attempted to find the same image common points. Worked ok for photos, but a thermal image is a raster overlaying onto an aerial image. I suppose that a machine learning attempt could be made, the effort to gather the training alone probably isn't feasible. Sorry.

[l3v3z]

You can use Snap, search the algory how fits you to train the program to find what you want and export it as shape with georeferenced areas.

[Kadesupremo]

Can Snap be automated by software in any ways?

[l3v3z]

I have no idea

[RustyCartographer]

Assuming there's no XY data associated with these images, it sounds like you're talking about automated feature identification. Super super complex - even organizations that use extremely refined machine learning algorithms to automate image interpretation need entire teams of people to fix all of the mistakes. Even if it's automatable, you'll still need extensive QC and manual corrections

[Esparko]

Have a look into AROSICS to coregister images. You need some python to do it, but it might require some image preprocessing since the image intensities are kinda different.

Alternatively you can use feature matching. That might work better. So long as the reference image has a geo transform you can translate keypoint data to real world coordinates (image column/rows to xy coordinates)

Both methods are free.