32 lines
1.3 KiB
Markdown
32 lines
1.3 KiB
Markdown
# Deconvolution
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Restore an image via regularised deconvolution. Assumes the image was blurred by a Gaussian PSF with the given sigma. Equivalent to Gwyddion's deconvolve.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 blurred field |
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## Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| restored | DATA_FIELD | Deconvolved (sharpened) field |
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## Controls
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| Name | Type | Default | Description |
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|------|------|---------|-------------|
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| method | dropdown | wiener | Deconvolution method: wiener or richardson_lucy |
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| sigma | FLOAT | 2.0 | Gaussian PSF sigma in pixels (0.1-50.0) |
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| regularisation | FLOAT | 0.01 | Regularisation parameter for Wiener filter (1e-6-1.0) |
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| iterations | INT | 10 | Number of iterations (Richardson-Lucy only, 1-200) |
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## Notes
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- **Wiener**: Fast, single-pass frequency-domain filter. The regularisation parameter controls the noise/sharpness tradeoff — smaller values sharpen more but amplify noise.
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- **Richardson-Lucy**: Iterative method that preserves positivity. More iterations = sharper result but risk of ringing artifacts.
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- The PSF sigma should match the actual blur in the image. If unknown, start with sigma=1-3 and adjust.
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- For tip-shape deconvolution (non-Gaussian PSF), use Tip Deconvolution instead.
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