SoGradientOperatorProcessing3d Class Reference
[Gradient]

SoGradientOperatorProcessing3d engine provides different operators to extract the edges from a 3D image. More...

Inheritance diagram for SoGradientOperatorProcessing3d:

Public Types
enum	GradientOperator { CANNY_DERICHE = 0, CANNY = 1, GAUSSIAN = 2, SOBEL = 4, PREWITT = 3 }
enum	GradientMode { AMPLITUDE_MAX_OF_MAGS = 0, X_Y_AND_Z_GRADIENTS = 1, AMPLITUDE_EUCLIDEAN = 2 }
Public Member Functions
	SoGradientOperatorProcessing3d ()
Public Attributes
SoSFImageDataAdapter	inImage
SoSFEnum	gradientOperator
SoSFEnum	gradientMode
SoSFFloat	standardDeviation
SoImageVizEngineOutput < SoSFImageDataAdapter, SoImageDataAdapter * >	outGradientXImage
SoImageVizEngineOutput < SoSFImageDataAdapter, SoImageDataAdapter * >	outGradientYImage
SoImageVizEngineOutput < SoSFImageDataAdapter, SoImageDataAdapter * >	outGradientZImage
SoImageVizEngineOutput < SoSFImageDataAdapter, SoImageDataAdapter * >	outAmplitudeImage

Detailed Description

SoGradientOperatorProcessing3d engine provides different operators to extract the edges from a 3D image.

For an introduction, see:

The SoGradientOperatorProcessing3d engine provides different operators to extract the edges from an image:

Canny-Deriche: It performs a recursive gradient computation to get the gradient in X, Y and Z directions. It is an FIR (finite impulse response) filter. To minimize the effect of noise, it smooths the image before computing the gradient. A smoothing scale parameter determines the smoothing intensity. If the value is large, noise will be reduced but edges will be less sharp and only the most significant edges will survive. It is important to select the right coefficient to lower the noise just enough without defocusing the edges. Then it gets the maximum of these images with a gradient magnitude operation. For color images it calculates the maximum of intensity or the euclidian mean.

Canny: It performs an approximation of to get the Canny Deriche in X and Y directions using a convolution kernel 7x5x5 for X, 5x7x5 for Y and 5x5x7 for Z. The result is nearly the same as with Canny Deriche but the processing is much faster.

Gaussian: It performs a convolution with the derivatives of a gaussian function along each image axis.

Sobel: It performs a convolution with the Sobel Kernel. This kernel is the 3D generalization of the Sobel kernel described in SoGradientOperatorProcessing2d

Prewitt: It performs a convolution with the Prewitt Kernel. This kernel is the 3D generalization of the Prewitt kernel described in SoGradientOperatorProcessing2d

Library references: gradient3d

Enumerator:

AMPLITUDE_MAX_OF_MAGS

This option computes the gradient maximal amplitude.

Only the outAmplitudeImage output is set using this mode.

X_Y_AND_Z_GRADIENTS

This option computes gradient in X, Y and Z directions.

AMPLITUDE_EUCLIDEAN

This option computes the euclidean amplitude gradient.

outAmplitudeImage output is set using this mode.

Enumerator:

CANNY_DERICHE	The gradient is computed using the Canny-Deriche algorithm. Supported gradient output modes : AMPLITUDE_MAX_OF_MAGS, and X_Y_AND_Z_GRADIENTS.
CANNY	The gradient is computed using the Canny algorithm. Supported gradient output modes : AMPLITUDE_MAX_OF_MAGS.
GAUSSIAN	The gradient is computed using the Gaussian algorithm. Supported gradient output modes : AMPLITUDE_MAX_OF_MAGS and X_Y_AND_Z_GRADIENTS.
SOBEL	The gradient is computed using the Sobel algorithm. Supported gradient output modes : AMPLITUDE_MAX_OF_MAGS and X_Y_AND_Z_GRADIENTS.
PREWITT	The gradient is computed using the Prewitt algorithm. Supported gradient output modes : AMPLITUDE_MAX_OF_MAGS and X_Y_AND_Z_GRADIENTS.