30 lines
1.1 KiB
Markdown
30 lines
1.1 KiB
Markdown
# Outlier Mask
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Create a mask marking pixels that deviate more than N standard deviations from the mean. Quick way to identify noise spikes and defects. Equivalent to Gwyddion's outliers.c module.
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## Inputs
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| Name | Type | Required | Description |
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|------|------|----------|-------------|
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| field | DATA_FIELD | Yes | Input surface |
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## Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| mask | IMAGE | Binary mask of outlier pixels |
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## Controls
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| Name | Type | Default | Description |
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|------|------|---------|-------------|
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| sigma_threshold | FLOAT | 3.0 | Number of standard deviations beyond which a pixel is an outlier (1.0–10.0) |
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| mode | dropdown | both | Which outliers to flag: both (high and low), high only, or low only |
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## Notes
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- A pixel is flagged if its z-score (data - mean) / std exceeds the threshold.
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- 3σ catches ~0.3% of pixels in a Gaussian distribution. Use 2σ for aggressive filtering or 5σ for conservative.
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- The resulting mask can be fed to Laplace Interpolation or Fractal Interpolation to fill the defects.
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- For a uniform (constant) field, no pixels are flagged regardless of threshold.
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