SoGaussianFilterProcessing Class Reference
[Smoothing And Denoising]

SoGaussianFilterProcessing engine More...

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

Inheritance diagram for SoGaussianFilterProcessing:

Public Types
enum	KernelType { SEPARABLE = 0, STANDARD = 1 }
Public Member Functions
	SoGaussianFilterProcessing ()
Public Attributes
SoSFEnum	computeMode
SoSFVec3f	standardDeviation
SoSFImageDataAdapter	inImage
SoSFEnum	kernelType
SoSFVec3i32	kernelSize
SoSFBool	autoScale
SoImageVizEngineOutput < SoSFImageDataAdapter, SoImageDataAdapter * >	outImage

Detailed Description

SoGaussianFilterProcessing engine

The SoGaussianFilterProcessing engine smooths an image using a kernel based on a gaussian distribution.

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

This engine smooths an image using a kernel based on a gaussian distribution:

In the 2-D case:

$f(x,y)=\exp(\frac{-x^2}{2\times StddevX^2})\exp(\frac{-y^2}{2\times StddevY^2})$

In the 3-D case:

$f(x,y,z)=\exp(\frac{-x^2}{2\times StddevX^2})\exp(\frac{-y^2}{2\times StddevY^2})\exp(\frac{-z^2}{2\times StddevZ^2})$

The parameters $x$ , $y$ and $z$ represent the offsets from the center. If the standard deviations are important, the filter coefficients will be closed to each other's. This engine can work with a circular kernel (in such a case standard deviations are equal along axis and kernel size is automatically adapted) or with a rectangular one.

FILE FORMAT/DEFAULT

computeMode	MODE_AUTO
standardDeviation	2.0f 2.0f 2.0f
inImage	NULL
kernelType	SEPARABLE
kernelSize	9 9 9
autoScale	TRUE

Library references: gaussianfilter gaussianfilter3d

Deprecated:: Deprecated since Open Inventor 9800
Replaced by SoGaussianBlurFilterProcessing

Member Enumeration Documentation

enum SoGaussianFilterProcessing::KernelType

Enumerator:

SEPARABLE	This mode specifies a separable kernel type for gaussian smoothing.
STANDARD	This mode specifies a full rectangular kernel type for gaussian smoothing.