itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput > Class Template Reference

#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 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
Static Public Member Functions
static Pointer	New ()
Static Public Attributes
static const unsigned int	ImageDimension2 = InputImageType::ImageDimension
Protected Member Functions
	DiscreteGaussianDerivativeImageFunction ()
	DiscreteGaussianDerivativeImageFunction (const Self &)
void	operator= (const Self &)
void	PrintSelf (std::ostream &os, Indent indent) const
void	RecomputeGaussianKernel ()
	~DiscreteGaussianDerivativeImageFunction ()
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

---

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 &

)

[inline, protected]

Definition at line 209 of file itkDiscreteGaussianDerivativeImageFunction.h.

template<class TInputImage , class TOutput = double>

itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::~DiscreteGaussianDerivativeImageFunction

(

)

[inline, protected]

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

)

[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 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 &

)

[inline, protected]

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 [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::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

)

[inline, virtual]

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

)

[inline, virtual]

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.

---

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

• itkDiscreteGaussianDerivativeImageFunction.h