Filters (Spatial): Nonlinear Noise Reduction

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This algorithm provides a port of the SUSAN (Smallest Univalue Segment Assimilating Nucleus) low-level image processing program.

For information about SUSAN, see

SUSAN noise reduction uses nonlinear filtering to reduce noise in an image while preserving both the underlying structure and the edges and corners. It does this by averaging a voxel only with local voxels that have similar intensity.

Table 1 explains the possible responses that the SUSAN filter provides if it cannot determine the neighborhood and based on whether you selected the option of using the median.

Table 1. Possible responses of the SUSAN filter

Use median
SUSAN area
The SUSAN filter . . .
Uses the median of the pixel's 8 nearest neighbors in 2D images or 26 nearest neighbors in 3D images to estimate the pixel's correct value.
Uses sums taken over the local neighborhood, not including the center pixel itself, to estimate the pixel's correct value. This allows good reduction of impulse noise.
Not selected
Uses sums taken over the local neighborhood including the center pixel to estimate the pixel's correct value.
Not selected
Leaves the pixel unchanged.

Image types

You can apply this algorithm to black-and-white 2D, 2.5D, and 3D images.

Special notes


Applying the algorithm

To run this algorithm, complete the following steps:

  1. Open an image.
  2. Select Algorithms > Filter (spatial) > Nonlinear noise reduction. The Nonlinear Noise Reduction dialog box (Figure 1) opens.
  3. Complete the information in the dialog box.
  4. Click OK. The algorithm begins to run.
A pop-up window appears with the status. The following message appears
"Performing the nonlinear noise reduction." When the algorithm finishes running, the pop-up window closes.
Depending on whether you selected New image or Replace image, the results appear in a new window or replace the image to which the algorithm was applied.
Figure 1. Nonlinear Noise Reduction dialog box

Brightness threshold
Blurs edges of contrast smaller than this threshold. Reducing the brightness threshold gives less smoothing. The default value is 0.1 * (image maximum - image minimum).
Mask Gaussian SD (0 for flat response) mm
Determines the spatial extent of the smoothing (the default value is equal to the X resolution). For a small, fast, flat response with a 3 x 3 or 3 x 3 x 3 voxel mask, set the mask SD to 0.
Use median when neighborhood not found
By default, this check box is selected.
Process each slice independently
Smooths each slice of the dataset independently (applies only to 3D images).
New image
Shows the results of the algorithm in a new image window (default choice).
Replace image
Replaces the current active image with the newly calculated image.
Applies the algorithm according to the specifications in this dialog box.
Disregards any changes that you made in the dialog box and closes the dialog box.
Displays online help for this dialog box.

See also: