Wavelet Denoise
Denoise a DATA_FIELD using wavelet coefficient thresholding. BayesShrink adapts the threshold per sub-band; VisuShrink uses a global threshold. Equivalent to applying DWT from Gwyddion dwt.c with coefficient thresholding.
Inputs
| Name |
Type |
Required |
Description |
| field |
DATA_FIELD |
Yes |
Input field to denoise |
Outputs
| Name |
Type |
Description |
| denoised |
DATA_FIELD |
Denoised field |
Controls
| Name |
Type |
Default |
Description |
| wavelet |
dropdown |
db4 |
Wavelet family: db1 (Haar), db2, db4, db8, sym4, coif1, or bior1.3 |
| method |
dropdown |
BayesShrink |
Threshold estimation method: BayesShrink (per sub-band adaptive) or VisuShrink (global universal) |
| sigma |
FLOAT |
0.0 |
Noise level estimate in data units; 0 = automatic estimation (0–1.0) |
| mode |
dropdown |
soft |
Thresholding mode: soft (smooth shrinkage) or hard (zero below threshold) |
Limitations
- The field size should ideally be a power of two for best wavelet decomposition; other sizes are handled by padding.
- sigma = 0 triggers automatic noise estimation from the finest-scale wavelet coefficients; this may be inaccurate on strongly structured surfaces.
