#include <itkDiscreteGaussianDerivativeImageFunction.h>

Detailed Description

template<typename TInputImage, typename 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, https://www.vicomtech.org/en

This implementation was taken from the Insight Journal paper: https://www.insight-journal.org/browse/publication/179

See also: NeighborhoodOperator; ImageFunction

Definition at line 47 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

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

Public Types
using	ConstPointer = SmartPointer< const Self >

using	GaussianDerivativeOperatorArrayType = FixedArray< GaussianDerivativeOperatorType, Self::ImageDimension2 >

using	GaussianDerivativeOperatorType = itk::GaussianDerivativeOperator< TOutput, Self::ImageDimension2 >

using	InterpolationModeEnum = GaussianDerivativeOperatorEnums::InterpolationMode

using	KernelType = Neighborhood< TOutput, Self::ImageDimension2 >

using	OperatorImageFunctionPointer = typename OperatorImageFunctionType::Pointer

using	OperatorImageFunctionType = NeighborhoodOperatorImageFunction< InputImageType, TOutput >

using	OrderArrayType = FixedArray< unsigned int, Self::ImageDimension2 >

using	Pointer = SmartPointer< Self >

using	Self = DiscreteGaussianDerivativeImageFunction

using	Superclass = ImageFunction< TInputImage, TOutput, TOutput >

using	VarianceArrayType = FixedArray< double, Self::ImageDimension2 >

Public Types inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
using	ConstPointer = SmartPointer< const Self >

using	ContinuousIndexType = ContinuousIndex< TOutput, Self::ImageDimension >

using	CoordRepType = TOutput

using	IndexType = typename InputImageType::IndexType

using	IndexValueType = typename InputImageType::IndexValueType

using	InputImageConstPointer = typename InputImageType::ConstPointer

using	InputImageType = TInputImage

using	InputPixelType = typename InputImageType::PixelType

using	OutputType = TOutput

using	Pointer = SmartPointer< Self >

using	PointType = Point< TOutput, Self::ImageDimension >

using	Self = ImageFunction

using	Superclass = FunctionBase< Point< TOutput, Self::ImageDimension >, TOutput >

Public Types inherited from itk::FunctionBase< Point< TOutput, TInputImage::ImageDimension >, TOutput >
using	ConstPointer = SmartPointer< const Self >

using	InputType = Point< TOutput, TInputImage::ImageDimension >

using	OutputType = TOutput

using	Pointer = SmartPointer< Self >

using	Self = FunctionBase

using	Superclass = Object

Public Types inherited from itk::Object
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = Object

using	Superclass = LightObject

Public Types inherited from itk::LightObject
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = LightObject

Public Member Functions
OutputType	Evaluate (const PointType &point) const override

OutputType	EvaluateAtContinuousIndex (const ContinuousIndexType &index) const override

OutputType	EvaluateAtIndex (const IndexType &index) const override

const char *	GetNameOfClass () const override

virtual void	Initialize ()

void	SetInputImage (const InputImageType *ptr) override

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	SetUseImageSpacing (bool _arg)

virtual bool	GetUseImageSpacing () const

virtual void	UseImageSpacingOn ()


virtual void	SetMaximumKernelWidth (unsigned int _arg)

virtual unsigned int	GetMaximumKernelWidth () const


virtual void	SetInterpolationMode (const InterpolationModeEnum _arg)

virtual InterpolationModeEnum	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

virtual const ContinuousIndexType &	GetEndContinuousIndex () const

virtual const IndexType &	GetEndIndex () const

const InputImageType *	GetInputImage () const

const char *	GetNameOfClass () const override

virtual const ContinuousIndexType &	GetStartContinuousIndex () const

virtual const IndexType &	GetStartIndex () const

virtual bool	IsInsideBuffer (const IndexType &index) const

virtual bool	IsInsideBuffer (const ContinuousIndexType &index) const

virtual bool	IsInsideBuffer (const PointType &point) const

void	ConvertPointToNearestIndex (const PointType &point, IndexType &index) const

Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)

unsigned long	AddObserver (const EventObject &event, Command *) const

unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const

LightObject::Pointer	CreateAnother () const override

virtual void	DebugOff () const

virtual void	DebugOn () const

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	GetMTime () const

virtual const TimeStamp &	GetTimeStamp () const

bool	HasObserver (const EventObject &event) const

void	InvokeEvent (const EventObject &)

void	InvokeEvent (const EventObject &) const

virtual void	Modified () const

void	Register () const override

void	RemoveAllObservers ()

void	RemoveObserver (unsigned long tag)

void	SetDebug (bool debugFlag) const

void	SetReferenceCount (int) override

void	UnRegister () const noexcept override

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)

virtual void	SetObjectName (std::string _arg)

virtual const std::string &	GetObjectName () const

Public Member Functions inherited from itk::LightObject
Pointer	Clone () const

virtual void	Delete ()

virtual int	GetReferenceCount () const

void	Print (std::ostream &os, Indent indent=0) const

Static Public Member Functions
static Pointer	New ()

Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()

static void	GlobalWarningDisplayOff ()

static void	GlobalWarningDisplayOn ()

static Pointer	New ()

static void	SetGlobalWarningDisplay (bool val)

Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

static Pointer	New ()

Static Public Attributes
static constexpr unsigned int	ImageDimension2 = InputImageType::ImageDimension

Static Public Attributes inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
static constexpr unsigned int	ImageDimension

Protected Member Functions
	DiscreteGaussianDerivativeImageFunction ()

	DiscreteGaussianDerivativeImageFunction (const Self &)

void	operator= (const Self &)

void	PrintSelf (std::ostream &os, Indent indent) const override

void	RecomputeGaussianKernel ()

	~DiscreteGaussianDerivativeImageFunction () override=default

Protected Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
	ImageFunction ()

void	PrintSelf (std::ostream &os, Indent indent) const override

	~ImageFunction () override=default

Protected Member Functions inherited from itk::FunctionBase< Point< TOutput, TInputImage::ImageDimension >, TOutput >
	FunctionBase ()=default

	~FunctionBase () override=default

Protected Member Functions inherited from itk::Object
	Object ()

bool	PrintObservers (std::ostream &os, Indent indent) const

virtual void	SetTimeStamp (const TimeStamp &timeStamp)

	~Object () override

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 {}

InterpolationModeEnum	m_InterpolationMode { InterpolationModeEnum::NearestNeighbourInterpolation }

double	m_MaximumError { 0.005 }

unsigned int	m_MaximumKernelWidth { 30 }

bool	m_NormalizeAcrossScale { true }

GaussianDerivativeOperatorArrayType	m_OperatorArray {}

OperatorImageFunctionPointer	m_OperatorImageFunction {}

OrderArrayType	m_Order {}

bool	m_UseImageSpacing { true }

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

Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount {}

Member Typedef Documentation

◆ ConstPointer

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::ConstPointer = SmartPointer<const Self>

Definition at line 59 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ GaussianDerivativeOperatorArrayType

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorArrayType = FixedArray<GaussianDerivativeOperatorType, Self::ImageDimension2>

Array to store gaussian derivative operators one for each dimension.

Definition at line 88 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ GaussianDerivativeOperatorType

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorType = itk::GaussianDerivativeOperator<TOutput, Self::ImageDimension2>

Definition at line 85 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ InterpolationModeEnum

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::InterpolationModeEnum = GaussianDerivativeOperatorEnums::InterpolationMode

Definition at line 98 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ KernelType

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::KernelType = Neighborhood<TOutput, Self::ImageDimension2>

Precomputed N-dimensional derivative kernel.

Definition at line 91 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ OperatorImageFunctionPointer

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OperatorImageFunctionPointer = typename OperatorImageFunctionType::Pointer

Definition at line 96 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ OperatorImageFunctionType

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OperatorImageFunctionType = NeighborhoodOperatorImageFunction<InputImageType, TOutput>

Image function that performs convolution with the neighborhood operator.

Definition at line 95 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ OrderArrayType

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OrderArrayType = FixedArray<unsigned int, Self::ImageDimension2>

Definition at line 83 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ Pointer

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Pointer = SmartPointer<Self>

Smart pointer type alias support

Definition at line 58 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ Self

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Self = DiscreteGaussianDerivativeImageFunction

Standard "Self" type alias

Definition at line 52 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ Superclass

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Superclass = ImageFunction<TInputImage, TOutput, TOutput>

Standard "Superclass" type alias

Definition at line 55 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ VarianceArrayType

template<typename TInputImage , typename TOutput = double>

using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::VarianceArrayType = FixedArray<double, Self::ImageDimension2>

Arrays for native types.

Definition at line 82 of file itkDiscreteGaussianDerivativeImageFunction.h.

Constructor & Destructor Documentation

◆ DiscreteGaussianDerivativeImageFunction() [1/2]

template<typename TInputImage , typename TOutput = double>

itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::DiscreteGaussianDerivativeImageFunction ( )

protected

◆ DiscreteGaussianDerivativeImageFunction() [2/2]

template<typename TInputImage , typename TOutput = double>

itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::DiscreteGaussianDerivativeImageFunction ( const Self & )

inlineprotected

Definition at line 218 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ ~DiscreteGaussianDerivativeImageFunction()

template<typename TInputImage , typename TOutput = double>

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

overrideprotecteddefault

Member Function Documentation

◆ Evaluate()

template<typename TInputImage , typename TOutput = double>

OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Evaluate ( const PointType & point ) const

overridevirtual

Evaluate the function at specified point.

Implements itk::ImageFunction< TInputImage, TOutput, TOutput >.

◆ EvaluateAtContinuousIndex()

template<typename TInputImage , typename TOutput = double>

OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::EvaluateAtContinuousIndex ( const ContinuousIndexType & index ) const

overridevirtual

Evaluate the function at specified ContinuousIndex position.

Implements itk::ImageFunction< TInputImage, TOutput, TOutput >.

◆ EvaluateAtIndex()

template<typename TInputImage , typename TOutput = double>

OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::EvaluateAtIndex ( const IndexType & index ) const

overridevirtual

Evaluate the function at specified Index position

Implements itk::ImageFunction< TInputImage, TOutput, TOutput >.

◆ GetInterpolationMode()

template<typename TInputImage , typename TOutput = double>

virtual InterpolationModeEnum itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetInterpolationMode ( ) const

virtual

Set/Get the interpolation mode.

◆ GetMaximumError()

template<typename TInputImage , typename 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.

◆ GetMaximumKernelWidth()

template<typename TInputImage , typename 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.

◆ GetNameOfClass()

template<typename TInputImage , typename TOutput = double>

const char* itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetNameOfClass ( ) const

overridevirtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::Object.

◆ GetNormalizeAcrossScale()

template<typename TInputImage , typename 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.

◆ GetOrder()

template<typename TInputImage , typename TOutput = double>

virtual const OrderArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetOrder ( ) const

virtual

Set/Get the derivative order for an individual dimension.

◆ GetUseImageSpacing()

template<typename TInputImage , typename TOutput = double>

virtual bool itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetUseImageSpacing ( ) const

virtual

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

◆ GetVariance()

template<typename TInputImage , typename 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.

◆ Initialize()

template<typename TInputImage , typename TOutput = double>

virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Initialize ( )

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 211 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ New()

template<typename TInputImage , typename TOutput = double>

static Pointer itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::New ( )

static

Method for creation through the object factory.

◆ NormalizeAcrossScaleOn()

template<typename TInputImage , typename 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.

◆ operator=()

template<typename TInputImage , typename TOutput = double>

void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::operator= ( const Self & )

inlineprotected

Definition at line 223 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ PrintSelf()

template<typename TInputImage , typename TOutput = double>

void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const

overrideprotectedvirtual

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::Object.

◆ RecomputeGaussianKernel()

template<typename TInputImage , typename TOutput = double>

void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::RecomputeGaussianKernel ( )

protected

◆ SetInputImage()

template<typename TInputImage , typename TOutput = double>

void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetInputImage ( const InputImageType * ptr )

overridevirtual

Set the input image.

Warning: this method caches BufferedRegion information. If the BufferedRegion has changed, user must call SetInputImage again to update cached values.

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

◆ SetInterpolationMode()

template<typename TInputImage , typename TOutput = double>

virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetInterpolationMode ( const InterpolationModeEnum _arg )

virtual

Set/Get the interpolation mode.

◆ SetMaximumError()

template<typename TInputImage , typename 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.

◆ SetMaximumKernelWidth()

template<typename TInputImage , typename 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.

◆ SetNormalizeAcrossScale()

template<typename TInputImage , typename 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.

◆ SetOrder() [1/3]

template<typename TInputImage , typename TOutput = double>

virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetOrder ( OrderArrayType _arg )

virtual

Set/Get the derivative order for an individual dimension.

◆ SetOrder() [2/3]

template<typename TInputImage , typename TOutput = double>

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

virtual

Set/Get the derivative order for an individual dimension.

◆ SetOrder() [3/3]

template<typename TInputImage , typename 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 166 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ SetSigma()

template<typename TInputImage , typename 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 143 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ SetUseImageSpacing()

template<typename TInputImage , typename TOutput = double>

virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetUseImageSpacing ( bool _arg )

virtual

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

◆ SetVariance() [1/3]

template<typename TInputImage , typename 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.

◆ SetVariance() [2/3]

template<typename TInputImage , typename TOutput = double>

virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetVariance ( double variance )

inlinevirtual

Convenience method for setting the variance for all dimensions.

Definition at line 132 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ SetVariance() [3/3]

template<typename TInputImage , typename 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.

◆ UseImageSpacingOn()

template<typename TInputImage , typename TOutput = double>

virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::UseImageSpacingOn ( )

virtual

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

Member Data Documentation

◆ ImageDimension2

template<typename TInputImage , typename TOutput = double>

constexpr unsigned int itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::ImageDimension2 = InputImageType::ImageDimension

staticconstexpr

Dimension of the underlying image.

Definition at line 76 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_DerivativeKernel

template<typename TInputImage , typename 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 252 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_InterpolationMode

template<typename TInputImage , typename TOutput = double>

InterpolationModeEnum itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_InterpolationMode { InterpolationModeEnum::NearestNeighbourInterpolation }

private

Interpolation mode.

Definition at line 264 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_MaximumError

template<typename TInputImage , typename TOutput = double>

double itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_MaximumError { 0.005 }

private

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

Definition at line 240 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_MaximumKernelWidth

template<typename TInputImage , typename TOutput = double>

unsigned int itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_MaximumKernelWidth { 30 }

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 245 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_NormalizeAcrossScale

template<typename TInputImage , typename TOutput = double>

bool itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_NormalizeAcrossScale { true }

private

Flag for scale-space normalization of derivatives.

Definition at line 258 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_OperatorArray

template<typename TInputImage , typename TOutput = double>

GaussianDerivativeOperatorArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_OperatorArray {}

private

Array of derivative operators, one for each dimension.

Definition at line 248 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_OperatorImageFunction

template<typename TInputImage , typename TOutput = double>

OperatorImageFunctionPointer itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_OperatorImageFunction {}

private

OperatorImageFunction

Definition at line 255 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_Order

template<typename TInputImage , typename TOutput = double>

OrderArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_Order {}

private

Order of the derivatives in each dimension.

Definition at line 236 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_UseImageSpacing

template<typename TInputImage , typename TOutput = double>

bool itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_UseImageSpacing { true }

private

Flag to indicate whether to use image spacing

Definition at line 261 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ m_Variance

template<typename TInputImage , typename TOutput = double>

VarianceArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::m_Variance {}

private

Desired variance of the discrete Gaussian function.

Definition at line 233 of file itkDiscreteGaussianDerivativeImageFunction.h.

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

itkDiscreteGaussianDerivativeImageFunction.h

Detailed Description

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

Public Types

Public Member Functions

Static Public Member Functions

Static Public Attributes

Protected Member Functions

Private Attributes

Additional Inherited Members

Member Typedef Documentation

◆ ConstPointer

◆ GaussianDerivativeOperatorArrayType

◆ GaussianDerivativeOperatorType

◆ InterpolationModeEnum

◆ KernelType

◆ OperatorImageFunctionPointer

◆ OperatorImageFunctionType

◆ OrderArrayType

◆ Pointer

◆ Self

◆ Superclass

◆ VarianceArrayType

Constructor & Destructor Documentation

◆ DiscreteGaussianDerivativeImageFunction() [1/2]

◆ DiscreteGaussianDerivativeImageFunction() [2/2]

◆ ~DiscreteGaussianDerivativeImageFunction()

Member Function Documentation

◆ Evaluate()

◆ EvaluateAtContinuousIndex()

◆ EvaluateAtIndex()

◆ GetInterpolationMode()

◆ GetMaximumError()

◆ GetMaximumKernelWidth()

◆ GetNameOfClass()

◆ GetNormalizeAcrossScale()

◆ GetOrder()

◆ GetUseImageSpacing()

◆ GetVariance()

◆ Initialize()

◆ New()

◆ NormalizeAcrossScaleOn()

◆ operator=()

◆ PrintSelf()

◆ RecomputeGaussianKernel()

◆ SetInputImage()

◆ SetInterpolationMode()

◆ SetMaximumError()

◆ SetMaximumKernelWidth()

◆ SetNormalizeAcrossScale()

◆ SetOrder() [1/3]

◆ SetOrder() [2/3]

◆ SetOrder() [3/3]

◆ SetSigma()

◆ SetUseImageSpacing()

◆ SetVariance() [1/3]

◆ SetVariance() [2/3]

◆ SetVariance() [3/3]

◆ UseImageSpacingOn()

Member Data Documentation

◆ ImageDimension2

◆ m_DerivativeKernel

◆ m_InterpolationMode

◆ m_MaximumError

◆ m_MaximumKernelWidth

◆ m_NormalizeAcrossScale

◆ m_OperatorArray

◆ m_OperatorImageFunction

◆ m_Order

◆ m_UseImageSpacing

◆ m_Variance

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