SoBoxFilterProcessing Class Reference
[Smoothing And Denoising]

ImageViz SoBoxFilterProcessing engine More...

#include <ImageViz/Engines/ImageFiltering/SmoothingAndDenoising/SoBoxFilterProcessing.h>

Inheritance diagram for SoBoxFilterProcessing:
SoImageVizEngine SoEngine SoFieldContainer SoBase SoRefCounter SoTypedObject

List of all members.

Public Member Functions

 SoBoxFilterProcessing ()

Public Attributes

SoSFEnum computeMode
SoSFVec3i32 kernelSize
SoSFImageDataAdapter inImage
SoSFBool autoScale
SoImageVizEngineOutput
< SoSFImageDataAdapter,
SoImageDataAdapter * > 
outImage

Detailed Description

ImageViz SoBoxFilterProcessing engine

The SoBoxFilterProcessing engine smooths an image using a box kernel.

For an introduction to image filters, see section Images Filters.

This engine performs a lowpass filter using the same box kernel as a lowpass filter. Yet, with this module, size in X, Y and Z may be different and larger than 7.

The algorithm calculates the local mean in a given size window. In the 3-D case, for a window of size 2p+1 in X, 2q+1 in Y and 2r+1 in Z:

\[O(n,m,o)=\frac{1}{K}\sum_{i=-p}^{p}\sum_{j=-q}^{q}\sum_{k=-r}^{r} I(n-i,m-j,o-k)\]

The K coefficient is the Normalization coefficient:

SEE ALSO

SoRecursiveExponentialFilterProcessing.

FILE FORMAT/DEFAULT


Library references: boxfilter boxfilter3d


Constructor & Destructor Documentation

SoBoxFilterProcessing::SoBoxFilterProcessing (  ) 

Constructor.


Member Data Documentation

Select the automatic intensity scaling mode.

Default value is TRUE.

Select the compute Mode (2D or 3D or AUTO) Use enum ComputeMode.

Default is MODE_AUTO

The input grayscale image.

Default value is NULL. Supported types include: grayscale binary label image.

The kernel size in each direction.

Default value is SbVec3i32(3,3,3)

The output image.

Default value is NULL. Supported types include: grayscale binary label color image.


The documentation for this class was generated from the following file:

Open Inventor Toolkit reference manual, generated on 4 Sep 2023
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