Sharpening algorithms might be statically defined rather than a bunch of weights, but they take a blurred image and create new data in it through approximations and heuristics defined in the algorithm.
I agree that it feels like there should be a difference, but I can't pin down what that actually is.
> create new data in it through approximations and heuristics defined in the algorithm
I guess the difference is where the algorithm gets it's input data from. Just sensor data or does it draw from a neural network that memorized a bunch of images / data store of images too.
You can argue what's the difference between this and Huawei replacing the image of the moon when their phone detects it with a hi-res one it has in storage - it's an "algorithm" too.
Are you using just the data provided to draw conclusions? Or do you include extra data from elsewhere to get your conclusions?
Sharpening algorithms might be statically defined rather than a bunch of weights, but they take a blurred image and create new data in it through approximations and heuristics defined in the algorithm.
I agree that it feels like there should be a difference, but I can't pin down what that actually is.