Welcome to PSF Hell

Today I learned about the Point Spread Function (PSF). In simple terms, it's how a star (a point of light) gets "smeared out" by the atmosphere and telescope optics. The problem? This smearing effect is different for each filter band (g, r, i, etc.).


For a neural network to properly compare colors, the images need to have a consistent "blurriness." This means I have to perform PSF matching: taking the sharpest image and deliberately blurring it to match the fuzziest one. It feels completely counterintuitive, and the math is giving me flashbacks to my toughest signal processing classes.

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