The Normalization Nightmare

How hard can it be to scale pixel values to a nice range for a neural network, like 0 to 1? Turns out, it's incredibly hard when dealing with astronomical data.

Min-Max Scaling? A single hot pixel or cosmic ray outlier will completely wreck the scale for the entire image.

Z-score Standardization? This works better but can result in negative values, which some neural network architectures don't like.

Asinh Stretch? This is what astronomers use to visualize images, as it handles the huge dynamic range. It's fantastic for making pretty pictures, but trying to explain it to PyTorch is another story.