Subframe Selector: Analysing and Weighting Your Data

Introduction

After Blink has removed the obviously bad frames, there’s one more powerful step before stacking: PixInsight’s Subframe Selector. This process doesn’t rely on guesswork or just your eyes. Instead, it measures the quality of every single subframe using hard numbers and allows you to either reject weaker ones or weight the strongest subs so they contribute more to the final image.

Think of Blink as the quick visual check, and Subframe Selector as the detailed quality control.

How to Open Subframe Selector

Finding Subframe Selector can be confusing if you haven’t used it before. Here’s exactly where to look:

1. In PixInsight, go to the top menu and click Process.
2. Navigate to:
   Process → Image Inspection → Subframe Selector
3. A new window will open with the tool’s interface.

📌 Alternative way:

• Open the Process Explorer panel on the left, expand Image Inspection and double-click SubframeSelector.

📌 If you still can’t see it:

• Go to Script → Feature Scripts → Search.
• Tick SubframeSelector if it appears and restart PixInsight.

📸 [Placeholder: Screenshot showing where Subframe Selector is located in the menu]

Why Use It?

Even frames that look fine in Blink can have subtle problems you won’t spot visually, such as:

• Slightly bloated stars
• Elliptical star shapes
• High background noise
• Transparency changes that affect signal strength

Subframe Selector measures all of these with:

• FWHM (Full Width Half Maximum): A measure of star size and focus. Lower = sharper.
• Eccentricity: How round the stars are. Lower values are better.
• Signal-to-Noise Ratio (SNR): Higher = cleaner, stronger signal.
• Background levels: Helps identify subs affected by haze or gradients.

Step-by-Step: Using Subframe Selector

1. Load Your Calibrated Lights
   • Drag your calibrated and Blink-approved subs into the Subframe Selector window.
2. Check Settings
   • You can usually leave the defaults, but if you know your pixel scale and focal length, enter them for more accurate results.
3. Measure the Frames
   • Click the Measure button.
   • PixInsight will analyse every subframe and produce a table of results.

📸 [Placeholder: Screenshot showing the results table after running measurements]

Understanding the Data (Made Simple)

• FWHM: Think of this as “sharpness”. Lower numbers mean tighter, more focused stars.
• Eccentricity: Measures star roundness. Around 0.4–0.5 is excellent. Higher than 0.65 usually means the stars are stretched or misshapen.
• SNR Weight: Tells you how much actual signal the frame contains compared to noise. Higher is better.

📸 [Placeholder: Graph screenshot highlighting FWHM and eccentricity]

What to do next:

• Look for frames that are obvious outliers (much higher FWHM or eccentricity).
• Right-click those frames and mark them for rejection.
• If you only have a small number of subs, you can choose to keep them but let weighting handle their impact.

Weighting Your Frames for Stacking

Subframe Selector can assign a weight to each sub so stacking scripts like WBPP give more importance to the highest quality frames.

1. Enable Weight Output
   • In the settings, tick “Output Subframe Weight keyword”.
2. Use a Weighting Formula
   • Copy and paste this into the Weighting Expression field: scssCopyEdit(SNRWeight/(FWHM^2)) * (1 - Eccentricity)
   • This formula rewards frames with high signal-to-noise, sharp stars, and low eccentricity.
3. Save or Tag the Frames
   • You can either move the approved subs into a new folder or just let the weights be saved as keywords for WBPP to use automatically.

📸 [Placeholder: Screenshot of weighting settings in Subframe Selector]

How Strict Should You Be?

• Large dataset: Be ruthless – keep only the best.
• Small dataset: Be more forgiving and rely on weighting.
• Golden rule: A few excellent frames will always beat lots of poor ones.

Where This Fits in the Workflow

Subframe Selector comes after Blink but before WBPP (or any stacking software). It’s your final quality check and optimisation stage before integration.

📸 [Placeholder: Workflow diagram – Lights → Calibration → Blink → Subframe Selector → WBPP → Integration]

Summary

• Subframe Selector is your second line of defence for data quality.
• It uses measurable data to help you reject or weight subs intelligently.
• Even if you keep all your frames, applying weights ensures the sharpest, cleanest subs dominate the final image.
• Mastering this stage will have a direct impact on the quality of your stacked results.