Aside from the paper, I think one thing they're referring to is using the output (color corrected images) as input for AI. One thing they want to do is count the number of fish in an image, and know which species each fish is. So you can take pictures of coral reefs and estimate "there's 1,000 species X, 2,200 species Y". With the old images, it's too difficult to determine which species a fish is. With the new images, it's easier. So Sea-Thru is preprocessing that'll be useful for AI in marine science.
I dont have the impression it works on moving objects, since it needs multiple frames from different depths, but it could be used to count static critters... unless some kind of boom with multiple cameras at different depths is used...
also, since the technique is removing a foggy haze, it seems like this could be used for selfdriving cars, with multiple cameras along the periphery of the car, to clean the image for foggy conditions (fog, smoke, smog, ...)
