Intermediate

Sigma-Clip Stacking

Statistical outlier rejection - for scientific-quality results

Quick Summary

Statistical outlier rejection - for scientific-quality results Default: 2.5 sigma threshold, 3 iterations. Lower sigma (2.0) = more aggressive rejection (use for severe contamination). Higher sigma (3.0) = more permissive (use for cleaner data). Each pixel is evaluated independently.

How Sigma-Clip Stacking Works

Calculates mean and standard deviation for each pixel across all frames

Values beyond 2.5 sigma (standard deviations) are flagged as outliers

Iterates 3 times to catch outliers that skewed initial statistics

Final image averages only the "normal" values

Best For

-Removing cosmic ray hits that appear as bright dots
-Cleaning hot pixels and column defects from uncooled sensors
-Videos contaminated with multiple satellite trails
-Scientific imaging where data integrity matters

Not Recommended For

-Very noisy footage where signal looks like noise to the algorithm
-Low frame count (<300) - statistics become unreliable
-When you want to preserve rare sharp details (they may be clipped)

Technical Details

Default: 2.5 sigma threshold, 3 iterations. Lower sigma (2.0) = more aggressive rejection (use for severe contamination). Higher sigma (3.0) = more permissive (use for cleaner data). Each pixel is evaluated independently.