3D Gaussian Smoothing

Overview

Applies Gaussian smoothing to the hyperspectral cube using a three-dimensional Gaussian filter.

Sigma controls the width of the Gaussian distribution. Larger sigma values produce stronger smoothing.

The filter size defines the Gaussian kernel dimensions. IDCubePro forces the value to an odd integer when required.

Because this is a 3D operation, smoothing can extend through both spatial and spectral dimensions.

• Spatial noise and spectral noise are both present.
• Mild multidimensional smoothing is desired.
• Small local fluctuations should be suppressed.

Strong 3D smoothing may broaden narrow spectral features, blur small spatial structures, or suppress weak signals.

Workflow

1. Load a hyperspectral dataset.

2. Open Correct > Filtering & Enhancement.

3. Select 3D Gaussian Smoothing.

4. Set Sigma and Filter Size.

5. Inspect the filtered image and spectra.

6. Use Reset Filters if the result is not desired.