I've spent years capturing the night sky, but the real magic happens during post-processing. After trying expensive commercial solutions, I've developed a workflow using entirely free, open-source tools that produces results rivaling those from $200+ software.

The challenge with astrophotography isn't just capturing faint light—it's extracting signal from noise, removing light pollution gradients, and enhancing details without introducing artifacts. These are fundamentally data processing problems that many engineers would find fascinating.

I've documented my complete workflow for processing deep space objects in GIMP, including:

Extracting maximum detail from RAW files using non-destructive editing Implementing a custom method for gradient removal without specialized plugins Using frequency separation techniques to enhance nebulosity while preserving star sharpness Building a reproducible workflow that maintains data integrity throughout The most surprising discovery was that proper masking and targeted adjustments often outperform the "auto" features in premium software. I've included before/after comparisons and the exact settings used.

What post-processing techniques have you found effective for extracting signal from noisy data? I'm curious if others have applied similar approaches to different domains.