ITK  4.1.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Static Public Attributes | Protected Member Functions | Private Attributes
itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput > Class Template Reference

#include <itkDiscreteGradientMagnitudeGaussianImageFunction.h>

+ Inheritance diagram for itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >:
+ Collaboration diagram for itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >:

List of all members.

Public Types

typedef SmartPointer< const SelfConstPointer
typedef
Superclass::ContinuousIndexType 
ContinuousIndexType
typedef FixedArray
< GaussianDerivativeOperatorType,
2 *itkGetStaticConstMacro(ImageDimension2) > 
GaussianDerivativeOperatorArrayType
typedef
itk::GaussianDerivativeOperator
< TOutput,
itkGetStaticConstMacro(ImageDimension2) > 
GaussianDerivativeOperatorType
typedef Superclass::IndexType IndexType
typedef Superclass::IndexValueType IndexValueType
typedef Superclass::InputImageType InputImageType
typedef Superclass::InputPixelType InputPixelType
enum  InterpolationModeType {
  NearestNeighbourInterpolation,
  LinearInterpolation
}
typedef FixedArray< KernelType,
itkGetStaticConstMacro(ImageDimension2) > 
KernelArrayType
typedef Neighborhood< TOutput,
itkGetStaticConstMacro(ImageDimension2) > 
KernelType
typedef
OperatorImageFunctionType::Pointer 
OperatorImageFunctionPointer
typedef
NeighborhoodOperatorImageFunction
< InputImageType, TOutput > 
OperatorImageFunctionType
typedef Superclass::OutputType OutputType
typedef SmartPointer< SelfPointer
typedef Superclass::PointType PointType
typedef
DiscreteGradientMagnitudeGaussianImageFunction 
Self
typedef ImageFunction
< TInputImage, TOutput,
TOutput > 
Superclass
typedef FixedArray< double,
itkGetStaticConstMacro(ImageDimension2) > 
VarianceArrayType
typedef FixedArray< unsigned
int, itkGetStaticConstMacro(ImageDimension2) > 
OrderArrayType

Public Member Functions

virtual ::itk::LightObject::Pointer CreateAnother (void) const
virtual OutputType Evaluate (const PointType &point) const
virtual OutputType EvaluateAtContinuousIndex (const ContinuousIndexType &index) const
virtual OutputType EvaluateAtIndex (const IndexType &index) const
virtual const char * GetNameOfClass () const
virtual void Initialize ()
virtual void SetInputImage (const InputImageType *ptr)
void SetSigma (const double sigma)
virtual void SetVariance (VarianceArrayType _arg)
virtual const VarianceArrayType GetVariance () const
virtual void SetVariance (double data[])
virtual void SetVariance (double variance)
virtual void SetMaximumError (double _arg)
virtual double GetMaximumError () const
virtual void SetNormalizeAcrossScale (bool _arg)
virtual bool GetNormalizeAcrossScale () const
virtual void NormalizeAcrossScaleOn ()
virtual void NormalizeAcrossScaleOff ()
virtual void SetUseImageSpacing (bool _arg)
virtual bool GetUseImageSpacing () const
virtual void UseImageSpacingOn ()
virtual void UseImageSpacingOff ()
virtual void SetMaximumKernelWidth (unsigned int _arg)
virtual unsigned int GetMaximumKernelWidth () const
virtual void SetInterpolationMode (InterpolationModeType _arg)
virtual InterpolationModeType GetInterpolationMode () const

Static Public Member Functions

static Pointer New ()

Static Public Attributes

static const unsigned int ImageDimension2 = InputImageType::ImageDimension

Protected Member Functions

 DiscreteGradientMagnitudeGaussianImageFunction ()
 DiscreteGradientMagnitudeGaussianImageFunction (const Self &)
void operator= (const Self &)
void PrintSelf (std::ostream &os, Indent indent) const
void RecomputeGaussianKernel ()
 ~DiscreteGradientMagnitudeGaussianImageFunction ()

Private Attributes

InterpolationModeType m_InterpolationMode
KernelArrayType m_KernelArray
double m_MaximumError
unsigned int m_MaximumKernelWidth
bool m_NormalizeAcrossScale
GaussianDerivativeOperatorArrayType m_OperatorArray
OperatorImageFunctionPointer m_OperatorImageFunction
bool m_UseImageSpacing
VarianceArrayType m_Variance

Detailed Description

template<class TInputImage, class TOutput = double>
class itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >

Compute the discrete gradient magnitude gaussian of an the image at a specific location in space, i.e. point, index or continuous index. This class computes a single derivative given the order in each direction (by default zero). This class is templated over the input image type.

The Initialize() method must be called after setting the parameters and before evaluating the function.

Author:
Ivan Macia, VICOMTech, Spain, http://www.vicomtech.es

This implementation was taken from the Insight Journal paper: http://hdl.handle.net/1926/1290

See also:
NeighborhoodOperator
ImageFunction

Definition at line 47 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.


Member Typedef Documentation

template<class TInputImage , class TOutput = double>
typedef SmartPointer< const Self > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ConstPointer
template<class TInputImage , class TOutput = double>
typedef Superclass::ContinuousIndexType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ContinuousIndexType
template<class TInputImage , class TOutput = double>
typedef FixedArray< GaussianDerivativeOperatorType, 2 *itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorArrayType

Array to store gaussian derivative operators one for each dimension

Definition at line 93 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef itk::GaussianDerivativeOperator< TOutput, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorType
template<class TInputImage , class TOutput = double>
typedef Superclass::IndexType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::IndexType
template<class TInputImage , class TOutput = double>
typedef Superclass::IndexValueType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::IndexValueType
template<class TInputImage , class TOutput = double>
typedef Superclass::InputImageType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::InputImageType
template<class TInputImage , class TOutput = double>
typedef Superclass::InputPixelType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::InputPixelType

InputPixel typedef support

Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.

Definition at line 70 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef FixedArray< KernelType, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::KernelArrayType

Array to store precomputed N-dimensional kernels for the gradient components

Definition at line 100 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Neighborhood< TOutput, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::KernelType

Precomputed N-dimensional derivative kernel

Definition at line 96 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef OperatorImageFunctionType::Pointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OperatorImageFunctionPointer
template<class TInputImage , class TOutput = double>
typedef NeighborhoodOperatorImageFunction< InputImageType, TOutput > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OperatorImageFunctionType

Image function that performs convolution with the neighborhood operator

Definition at line 104 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef FixedArray< unsigned int, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OrderArrayType

Arrays for native types

Definition at line 85 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Superclass::OutputType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OutputType
template<class TInputImage , class TOutput = double>
typedef SmartPointer< Self > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Pointer

Smart pointer typedef support

Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.

Definition at line 59 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Superclass::PointType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::PointType
template<class TInputImage , class TOutput = double>
typedef DiscreteGradientMagnitudeGaussianImageFunction itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Self

Standard "Self" typedef

Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.

Definition at line 53 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef ImageFunction< TInputImage, TOutput, TOutput > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Superclass

Standard "Superclass" typedef

Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.

Definition at line 56 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef FixedArray< double, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::VarianceArrayType

Arrays for native types

Definition at line 84 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.


Member Enumeration Documentation

template<class TInputImage , class TOutput = double>
enum itk::DiscreteGradientMagnitudeGaussianImageFunction::InterpolationModeType

Interpolation modes

Enumerator:
NearestNeighbourInterpolation 
LinearInterpolation 

Definition at line 108 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.


Constructor & Destructor Documentation

template<class TInputImage , class TOutput = double>
itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::DiscreteGradientMagnitudeGaussianImageFunction ( ) [protected]
template<class TInputImage , class TOutput = double>
itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::DiscreteGradientMagnitudeGaussianImageFunction ( const Self ) [inline, protected]
template<class TInputImage , class TOutput = double>
itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::~DiscreteGradientMagnitudeGaussianImageFunction ( ) [inline, protected]

Member Function Documentation

template<class TInputImage , class TOutput = double>
virtual::itk::LightObject::Pointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::CreateAnother ( void  ) const [virtual]

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::Object.

template<class TInputImage , class TOutput = double>
virtual OutputType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Evaluate ( const PointType point) const [virtual]

Evalutate the in the given dimension at specified point

template<class TInputImage , class TOutput = double>
virtual OutputType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::EvaluateAtContinuousIndex ( const ContinuousIndexType index) const [virtual]

Evaluate the function at specified ContinousIndex position

template<class TInputImage , class TOutput = double>
virtual OutputType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::EvaluateAtIndex ( const IndexType index) const [virtual]

Evaluate the function at specified Index position

template<class TInputImage , class TOutput = double>
virtual InterpolationModeType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetInterpolationMode ( ) const [virtual]

Set/Get the interpolation mode.

template<class TInputImage , class TOutput = double>
virtual double itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetMaximumError ( ) const [virtual]

Set/Get the desired maximum error of the gaussian approximation. Maximum error is the difference between the area under the discrete Gaussian curve and the area under the continuous Gaussian. Maximum error affects the Gaussian operator size. The value is clamped between 0.00001 and 0.99999.

template<class TInputImage , class TOutput = double>
virtual unsigned int itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetMaximumKernelWidth ( ) const [virtual]

Set/Get a limit for growth of the kernel. Small maximum error values with large variances will yield very large kernel sizes. This value can be used to truncate a kernel in such instances. A warning will be given on truncation of the kernel.

template<class TInputImage , class TOutput = double>
virtual const char* itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetNameOfClass ( ) const [virtual]

Run-time type information (and related methods)

Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.

template<class TInputImage , class TOutput = double>
virtual bool itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetNormalizeAcrossScale ( ) const [virtual]

Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.

template<class TInputImage , class TOutput = double>
virtual bool itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetUseImageSpacing ( ) const [virtual]

Set/Get the flag for using image spacing when calculating derivatives.

template<class TInputImage , class TOutput = double>
virtual const VarianceArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetVariance ( ) const [virtual]

Set/Get the variance for the discrete Gaussian kernel. Sets the variance for individual dimensions. The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Initialize ( void  ) [inline, virtual]

Initialize the Gaussian kernel. Call this method before evaluating the function. This method MUST be called after any changes to function parameters.

Definition at line 189 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
static Pointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::New ( ) [static]

Method for creation through the object factory

Reimplemented from itk::Object.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::NormalizeAcrossScaleOff ( ) [virtual]

Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::NormalizeAcrossScaleOn ( ) [virtual]

Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.

template<class TInputImage , class TOutput = double>
void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::operator= ( const Self ) [inline, protected]

Mutex lock to protect modification to the reference count

Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.

Definition at line 197 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::PrintSelf ( std::ostream &  os,
Indent  indent 
) const [protected, virtual]

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.

template<class TInputImage , class TOutput = double>
void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::RecomputeGaussianKernel ( ) [protected]
template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetInputImage ( const InputImageType ptr) [virtual]

Set the input image.

Warning:
this method caches BufferedRegion information. If the BufferedRegion has changed, user must call SetInputImage again to update cached values.
template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetInterpolationMode ( InterpolationModeType  _arg) [virtual]

Set/Get the interpolation mode.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetMaximumError ( double  _arg) [virtual]

Set/Get the desired maximum error of the gaussian approximation. Maximum error is the difference between the area under the discrete Gaussian curve and the area under the continuous Gaussian. Maximum error affects the Gaussian operator size. The value is clamped between 0.00001 and 0.99999.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetMaximumKernelWidth ( unsigned int  _arg) [virtual]

Set/Get a limit for growth of the kernel. Small maximum error values with large variances will yield very large kernel sizes. This value can be used to truncate a kernel in such instances. A warning will be given on truncation of the kernel.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetNormalizeAcrossScale ( bool  _arg) [virtual]

Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.

template<class TInputImage , class TOutput = double>
void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetSigma ( const double  sigma) [inline]

Convenience method for setting the variance through the standard deviation

Definition at line 140 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetUseImageSpacing ( bool  _arg) [virtual]

Set/Get the flag for using image spacing when calculating derivatives.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetVariance ( VarianceArrayType  _arg) [virtual]

Set/Get the variance for the discrete Gaussian kernel. Sets the variance for individual dimensions. The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetVariance ( double  data[]) [virtual]

Set/Get the variance for the discrete Gaussian kernel. Sets the variance for individual dimensions. The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetVariance ( double  variance) [inline, virtual]

Convenience method for setting the variance for all dimensions

Definition at line 131 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::UseImageSpacingOff ( ) [virtual]

Set/Get the flag for using image spacing when calculating derivatives.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::UseImageSpacingOn ( ) [virtual]

Set/Get the flag for using image spacing when calculating derivatives.


Member Data Documentation

template<class TInputImage , class TOutput = double>
const unsigned int itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ImageDimension2 = InputImageType::ImageDimension [static]

Dimension of the underlying image

Definition at line 78 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
InterpolationModeType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_InterpolationMode [private]

Interpolation mode

Definition at line 236 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
KernelArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_KernelArray [private]

Array of N-dimensional kernels used to calculate gradient components

Definition at line 224 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
double itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_MaximumError [private]

Difference between the areas under the curves of the continuous and discrete Gaussian functions

Definition at line 211 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
unsigned int itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_MaximumKernelWidth [private]

Maximum kernel size allowed. This value is used to truncate a kernel that has grown too large. A warning is given when the specified maximum error causes the kernel to exceed this size

Definition at line 216 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
bool itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_NormalizeAcrossScale [private]

Flag for scale-space normalization of derivatives

Definition at line 230 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
GaussianDerivativeOperatorArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_OperatorArray [private]

Array of derivative operators, one for each dimension and order. First N zero-rder operators are stored, then N first-order making 2*N operators altogether where N=ImageDimension

Definition at line 221 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
OperatorImageFunctionPointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_OperatorImageFunction [private]

OperatorImageFunction

Definition at line 227 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
bool itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_UseImageSpacing [private]

Flag to indicate whether to use image spacing

Definition at line 233 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

template<class TInputImage , class TOutput = double>
VarianceArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_Variance [private]

Desired variance of the discrete Gaussian function

Definition at line 207 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.


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