ITK  4.2.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Static Public Attributes | Protected Member Functions | Private Attributes
itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput > Class Template Reference
Module ITKReview

#include <itkDiscreteGaussianDerivativeImageFunction.h>

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

List of all members.

Public Types

typedef SmartPointer< const Self > ConstPointer
typedef
Superclass::ContinuousIndexType 		ContinuousIndexType
typedef FixedArray
< GaussianDerivativeOperatorType,
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 Neighborhood< TOutput,
itkGetStaticConstMacro(ImageDimension2) > 		KernelType
typedef
OperatorImageFunctionType::Pointer 		OperatorImageFunctionPointer
typedef
NeighborhoodOperatorImageFunction
< InputImageType, TOutput > 		OperatorImageFunctionType
typedef Superclass::OutputType OutputType
typedef SmartPointer< Self > Pointer
typedef Superclass::PointType PointType
typedef
DiscreteGaussianDerivativeImageFunction 		Self
typedef ImageFunction
< TInputImage, TOutput,
TOutput > 		Superclass
typedef FixedArray< double,
itkGetStaticConstMacro(ImageDimension2) > 		VarianceArrayType
typedef FixedArray< unsigned
int, itkGetStaticConstMacro(ImageDimension2) > 		OrderArrayType
- Public Types inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
typedef TOutput CoordRepType
typedef
InputImageType::ConstPointer 		InputImageConstPointer
- Public Types inherited from itk::FunctionBase< Point< TOutput, TInputImage::ImageDimension >, TOutput >
typedef Point< TOutput,
TInputImage::ImageDimension > 		InputType
- Public Types inherited from itk::Object
- Public Types inherited from itk::LightObject

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 SetOrder (OrderArrayType _arg)
virtual const OrderArrayType GetOrder () const
virtual void SetOrder (unsigned int data[])
virtual void SetOrder (unsigned int order)
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
- Public Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
void ConvertContinuousIndexToNearestIndex (const ContinuousIndexType &cindex, IndexType &index) const
void ConvertPointToContinuousIndex (const PointType &point, ContinuousIndexType &cindex) const
void ConvertPointToNearestIndex (const PointType &point, IndexType &index) const
virtual TOutput Evaluate (const PointType &point) const =0
virtual TOutput EvaluateAtContinuousIndex (const ContinuousIndexType &index) const =0
virtual TOutput EvaluateAtIndex (const IndexType &index) const =0
virtual const ContinuousIndexType & GetEndContinuousIndex ()
virtual const IndexType & GetEndIndex ()
const InputImageType * GetInputImage () const
virtual const ContinuousIndexType & GetStartContinuousIndex ()
virtual const IndexType & GetStartIndex ()
virtual void SetInputImage (const InputImageType *ptr)
virtual bool IsInsideBuffer (const IndexType &index) const
virtual bool IsInsideBuffer (const ContinuousIndexType &index) const
virtual bool IsInsideBuffer (const PointType &point) const

Static Public Member Functions

static Pointer New ()

Static Public Attributes

static const unsigned int ImageDimension2 = InputImageType::ImageDimension
- Static Public Attributes inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
static const unsigned int ImageDimension

Protected Member Functions

 DiscreteGaussianDerivativeImageFunction ()
 DiscreteGaussianDerivativeImageFunction (const Self &)
void operator= (const Self &)
void PrintSelf (std::ostream &os, Indent indent) const
void RecomputeGaussianKernel ()
 ~DiscreteGaussianDerivativeImageFunction ()
- Protected Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
 ImageFunction ()
 ~ImageFunction ()
- Protected Member Functions inherited from itk::FunctionBase< Point< TOutput, TInputImage::ImageDimension >, TOutput >
 FunctionBase ()
 ~FunctionBase ()
- Protected Member Functions inherited from itk::Object
 Object ()
bool PrintObservers (std::ostream &os, Indent indent) const
virtual void SetTimeStamp (const TimeStamp &time)
virtual ~Object ()
- Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer InternalClone () const
 LightObject ()
virtual void PrintHeader (std::ostream &os, Indent indent) const
virtual void PrintTrailer (std::ostream &os, Indent indent) const
virtual ~LightObject ()

Private Attributes

KernelType m_DerivativeKernel
InterpolationModeType m_InterpolationMode
double m_MaximumError
unsigned int m_MaximumKernelWidth
bool m_NormalizeAcrossScale
GaussianDerivativeOperatorArrayType m_OperatorArray
OperatorImageFunctionPointer m_OperatorImageFunction
OrderArrayType m_Order
bool m_UseImageSpacing
VarianceArrayType m_Variance

Additional Inherited Members

- Protected Attributes inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
ContinuousIndexType m_EndContinuousIndex
IndexType m_EndIndex
InputImageConstPointer m_Image
ContinuousIndexType m_StartContinuousIndex
IndexType m_StartIndex

Detailed Description

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

Compute the discrete gaussian derivatives 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 itkDiscreteGaussianDerivativeImageFunction.h.

Member Typedef Documentation

template<class TInputImage , class TOutput = double>
typedef SmartPointer< const Self > itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::ConstPointer

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

Definition at line 60 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Superclass::ContinuousIndexType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::ContinuousIndexType

ContinuousIndex Type.

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

Definition at line 73 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef FixedArray< GaussianDerivativeOperatorType, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorArrayType

Array to store gaussian derivative operators one for each dimension.

Definition at line 93 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef itk::GaussianDerivativeOperator< TOutput, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorType

Definition at line 89 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Superclass::IndexType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::IndexType

Index Type.

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

Definition at line 71 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Superclass::IndexValueType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::IndexValueType

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

Definition at line 72 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Superclass::InputImageType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::InputImageType

Image dependent types.

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

Definition at line 66 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Superclass::InputPixelType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::InputPixelType

InputPixel typedef support

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

Definition at line 70 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

Precomputed N-dimensional derivative kernel.

Definition at line 96 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef OperatorImageFunctionType::Pointer itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OperatorImageFunctionPointer

Definition at line 102 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef NeighborhoodOperatorImageFunction< InputImageType, TOutput > itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OperatorImageFunctionType

Image function that performs convolution with the neighborhood operator.

Definition at line 101 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

Arrays for native types.

Definition at line 85 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef Superclass::OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OutputType

Output type.

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

Definition at line 81 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef SmartPointer< Self > itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Pointer

Smart pointer typedef support.

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

Definition at line 59 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

Point Type.

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

Definition at line 74 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
typedef DiscreteGaussianDerivativeImageFunction itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Self

Standard "Self" typedef

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

Definition at line 53 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

Standard "Superclass" typedef

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

Definition at line 56 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

Arrays for native types.

Definition at line 84 of file itkDiscreteGaussianDerivativeImageFunction.h.

Member Enumeration Documentation

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

Interpolation modes.

Enumerator:
NearestNeighbourInterpolation 
LinearInterpolation 

Definition at line 105 of file itkDiscreteGaussianDerivativeImageFunction.h.

Constructor & Destructor Documentation

template<class TInputImage , class TOutput = double>
itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::DiscreteGaussianDerivativeImageFunction ( )
protected
template<class TInputImage , class TOutput = double>
itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::DiscreteGaussianDerivativeImageFunction ( const Self &  )
inlineprotected

Definition at line 209 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::~DiscreteGaussianDerivativeImageFunction ( )
inlineprotected

Definition at line 211 of file itkDiscreteGaussianDerivativeImageFunction.h.

Member Function Documentation

template<class TInputImage , class TOutput = double>
virtual::itk::LightObject::Pointer itk::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Evaluate ( const PointType &  point) const
virtual

Evaluate the function at specified point.

template<class TInputImage , class TOutput = double>
virtual OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::EvaluateAtContinuousIndex ( const ContinuousIndexType &  index) const
virtual

Evaluate the function at specified ContinousIndex position.

template<class TInputImage , class TOutput = double>
virtual OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::EvaluateAtIndex ( const IndexType &  index) const
virtual

Evaluate the function at specified Index position

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

Set/Get the interpolation mode.

template<class TInputImage , class TOutput = double>
virtual double itk::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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 const OrderArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetOrder ( ) const
virtual

Set/Get the derivative order for an individual dimension.

template<class TInputImage , class TOutput = double>
virtual bool itk::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Initialize ( void  )
inlinevirtual

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 205 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

Method for creation through the object factory.

Reimplemented from itk::Object.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::operator= ( const Self &  )
inlineprotected

Mutex lock to protect modification to the reference count

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

Definition at line 213 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
protectedvirtual

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::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::RecomputeGaussianKernel ( )
protected
template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetInterpolationMode ( InterpolationModeType  _arg)
virtual

Set/Get the interpolation mode.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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>
virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetOrder ( OrderArrayType  _arg)
virtual

Set/Get the derivative order for an individual dimension.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetOrder ( unsigned int  data[])
virtual

Set/Get the derivative order for an individual dimension.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetOrder ( unsigned int  order)
inlinevirtual

Convenience method for setting the order for all dimensions.

Definition at line 162 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

Convenience method for setting the variance through the standard deviation.

Definition at line 140 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetVariance ( double  variance)
inlinevirtual

Convenience method for setting the variance for all dimensions.

Definition at line 130 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

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

template<class TInputImage , class TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< 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::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::ImageDimension2 = InputImageType::ImageDimension
static

Dimension of the underlying image.

Definition at line 78 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
KernelType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_DerivativeKernel
private

N-dimensional kernel which is the result of convolving the operators for calculating derivatives.

Definition at line 240 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
InterpolationModeType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_InterpolationMode
private

Interpolation mode.

Definition at line 252 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
double itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_MaximumError
private

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

Definition at line 228 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
unsigned int itk::DiscreteGaussianDerivativeImageFunction< 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 233 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
bool itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_NormalizeAcrossScale
private

Flag for scale-space normalization of derivatives.

Definition at line 246 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
GaussianDerivativeOperatorArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_OperatorArray
private

Array of derivative operators, one for each dimension.

Definition at line 236 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
OperatorImageFunctionPointer itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_OperatorImageFunction
private

OperatorImageFunction

Definition at line 243 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
OrderArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_Order
private

Order of the derivatives in each dimension.

Definition at line 224 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
bool itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_UseImageSpacing
private

Flag to indicate whether to use image spacing

Definition at line 249 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>
VarianceArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_Variance
private

Desired variance of the discrete Gaussian function.

Definition at line 221 of file itkDiscreteGaussianDerivativeImageFunction.h.

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