Using machine learning to colourise grayscale images, is it being done? Options

[Habukaz]

I am just wondering whether machine learning is being used (by people here or elsewhere) to colourise space images that lack colour data (like MER Navcam images, LORRI images and so on).

I have a few ideas on how to do it; but if it is already routinely being done (and with good results), it wouldn't be as cool to try to implement them.

[JRehling]

Funny, I have been thinking recently on a related problem, to add texture to images of a given resolution after upscaling them so that resolution could be increased.

The basic truth, though, is: You can't get something for nothing. A BW photo of Uranus, Titan, and Venus might be exactly the same. You can color them by knowing the right answer, but it's absolutely impossible to extract color from the image itself. And the same principle applies on all levels.

I have colored a BW image that I took of Mars – that's quite predictable, on a global scale, but only because I know what the colors of Mars are.

If color is easily predictable from brightness alone, then this can be done. If not, it can't. And this will have to be world by world, nebula by nebula, etc.

I'd say that Mars and Europa, to choose a pair, make this quite possible at global resolution. Jupiter, for example, does not (the GRS is the same brightness as many non-red portions of it).