Intermediate

Weighted Quality Stacking

Your sharpest frames contribute most - ideal for variable seeing

Quick Summary

Your sharpest frames contribute most - ideal for variable seeing Uses Laplacian variance to measure high-frequency content (sharpness). Weights are normalized so maximum contribution is 3x average. This prevents a single perfect frame from overwhelming the noise-reduction benefit of stacking.

How Weighted Quality Stacking Works

Measures sharpness of each frame using Laplacian variance

Sharp frames get up to 3x more weight in the final average

Blurry frames contribute less, preserving detail from good moments

Weights are normalized to prevent any single frame dominating

Best For

-Nights with variable atmospheric seeing (most common scenario)
-Capturing those brief moments of excellent clarity
-Jupiter cloud bands and Saturn rings where micro-detail matters
-Videos longer than 30 seconds with varying quality

Not Recommended For

-Very short captures (<500 frames) - not enough variation to matter
-Uniformly excellent seeing - all frames similar quality
-Smartphone video where compression limits sharpness detection

Technical Details

Uses Laplacian variance to measure high-frequency content (sharpness). Weights are normalized so maximum contribution is 3x average. This prevents a single perfect frame from overwhelming the noise-reduction benefit of stacking.