#include <itkDiscreteGradientMagnitudeGaussianImageFunction.h>

Detailed Description

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

This implementation was taken from the Insight Journal paper: https://doi.org/10.54294/mrg5is

See also: NeighborhoodOperator; ImageFunction

Definition at line 47 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

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

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

Public Types
using	ConstPointer = SmartPointer<const Self>

using	GaussianDerivativeOperatorArrayType = FixedArray<GaussianDerivativeOperatorType, 2 * Self::ImageDimension2>

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

using	InterpolationModeEnum = itk::GaussianDerivativeOperatorEnums::InterpolationMode

using	KernelArrayType = FixedArray<KernelType, Self::ImageDimension2>

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 = DiscreteGradientMagnitudeGaussianImageFunction

using	Superclass = ImageFunction<TInputImage, TOutput, TOutput>

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

Public Types inherited from itk::ImageFunction< TInputImage, double, double >
using	ConstPointer

using	ContinuousIndexType

using	CoordinateType

using	IndexType

using	IndexValueType

using	InputImageConstPointer

using	InputImageType

using	InputPixelType

using	OutputType

using	Pointer

using	PointType

using	Self

using	Superclass

Public Types inherited from itk::FunctionBase< Point< double, TInputImage::ImageDimension >, double >
using	ConstPointer

using	InputType

using	OutputType

using	Pointer

using	Self

using	Superclass

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
virtual::itk::LightObject::Pointer	CreateAnother () const

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	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 (const InterpolationModeEnum _arg)

virtual InterpolationModeEnum	GetInterpolationMode () const

Public Member Functions inherited from itk::ImageFunction< TInputImage, double, double >
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::FunctionBase< Point< double, TInputImage::ImageDimension >, double >
virtual OutputType	Evaluate (const InputType &input) const=0

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

const char *	GetNameOfClass () const override

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) const

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, double, double >
static constexpr unsigned int	ImageDimension

Protected Member Functions
	DiscreteGradientMagnitudeGaussianImageFunction ()

	DiscreteGradientMagnitudeGaussianImageFunction (const Self &)

void	operator= (const Self &)

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

void	RecomputeGaussianKernel ()

	~DiscreteGradientMagnitudeGaussianImageFunction () override=default

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

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

	~ImageFunction () override=default

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

	~FunctionBase () override=default

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

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

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

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
InterpolationModeEnum	m_InterpolationMode { InterpolationModeEnum::NearestNeighbourInterpolation }

KernelArrayType	m_KernelArray {}

double	m_MaximumError { 0.005 }

unsigned int	m_MaximumKernelWidth { 30 }

bool	m_NormalizeAcrossScale { true }

GaussianDerivativeOperatorArrayType	m_OperatorArray {}

OperatorImageFunctionPointer	m_OperatorImageFunction {}

bool	m_UseImageSpacing { true }

VarianceArrayType	m_Variance {}

Additional Inherited Members
Protected Attributes inherited from itk::ImageFunction< TInputImage, double, double >
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::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ConstPointer = SmartPointer<const Self>

Definition at line 60 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ GaussianDerivativeOperatorArrayType

template<typename TInputImage, typename TOutput = double>

using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorArrayType = FixedArray<GaussianDerivativeOperatorType, 2 * Self::ImageDimension2>

Array to store gaussian derivative operators one for each dimension

Definition at line 89 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ GaussianDerivativeOperatorType

template<typename TInputImage, typename TOutput = double>

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

Definition at line 86 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ InterpolationModeEnum

template<typename TInputImage, typename TOutput = double>

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

Definition at line 102 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ KernelArrayType

template<typename TInputImage, typename TOutput = double>

using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::KernelArrayType = FixedArray<KernelType, Self::ImageDimension2>

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

Definition at line 96 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ KernelType

template<typename TInputImage, typename TOutput = double>

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

Precomputed N-dimensional derivative kernel

Definition at line 92 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ OperatorImageFunctionPointer

template<typename TInputImage, typename TOutput = double>

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

Definition at line 100 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ OperatorImageFunctionType

template<typename TInputImage, typename TOutput = double>

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

Image function that performs convolution with the neighborhood operator

Definition at line 99 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ OrderArrayType

template<typename TInputImage, typename TOutput = double>

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

Definition at line 84 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ Pointer

template<typename TInputImage, typename TOutput = double>

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

Smart pointer type alias support

Definition at line 59 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ Self

template<typename TInputImage, typename TOutput = double>

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

Standard "Self" type alias

Definition at line 53 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ Superclass

template<typename TInputImage, typename TOutput = double>

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

Standard "Superclass" type alias

Definition at line 56 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ VarianceArrayType

template<typename TInputImage, typename TOutput = double>

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

Arrays for native types

Definition at line 83 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

Constructor & Destructor Documentation

◆ DiscreteGradientMagnitudeGaussianImageFunction() [1/2]

template<typename TInputImage, typename TOutput = double>

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

protected

Referenced by GetNameOfClass().

◆ DiscreteGradientMagnitudeGaussianImageFunction() [2/2]

template<typename TInputImage, typename TOutput = double>

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

inlineprotected

Definition at line 202 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ ~DiscreteGradientMagnitudeGaussianImageFunction()

template<typename TInputImage, typename TOutput = double>

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

overrideprotecteddefault

Member Function Documentation

◆ CreateAnother()

template<typename TInputImage, typename TOutput = double>

virtual::itk::LightObject::Pointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::CreateAnother ( ) 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::LightObject.

◆ Evaluate()

template<typename TInputImage, typename TOutput = double>

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

overridevirtual

Evaluate the function in the given dimension at specified point

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

References itk::point().

◆ EvaluateAtContinuousIndex()

template<typename TInputImage, typename TOutput = double>

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

overridevirtual

Evaluate the function at specified ContinuousIndex position

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

◆ EvaluateAtIndex()

template<typename TInputImage, typename TOutput = double>

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

overridevirtual

Evaluate the function at specified Index position

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

◆ GetInterpolationMode()

template<typename TInputImage, typename TOutput = double>

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

virtual

Set/Get the interpolation mode.

◆ GetMaximumError()

template<typename TInputImage, typename 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.

◆ GetMaximumKernelWidth()

template<typename TInputImage, typename 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.

◆ GetNameOfClass()

template<typename TInputImage, typename TOutput = double>

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

overridevirtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::LightObject.

References DiscreteGradientMagnitudeGaussianImageFunction().

◆ GetNormalizeAcrossScale()

template<typename TInputImage, typename 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.

◆ GetUseImageSpacing()

template<typename TInputImage, typename TOutput = double>

virtual bool itk::DiscreteGradientMagnitudeGaussianImageFunction< 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::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

◆ Initialize()

template<typename TInputImage, typename TOutput = double>

virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< 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 195 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

References RecomputeGaussianKernel().

◆ New()

template<typename TInputImage, typename TOutput = double>

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

static

Method for creation through the object factory

◆ NormalizeAcrossScaleOff()

template<typename TInputImage, typename 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.

◆ NormalizeAcrossScaleOn()

template<typename TInputImage, typename 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.

◆ operator=()

template<typename TInputImage, typename TOutput = double>

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

inlineprotected

Definition at line 207 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ PrintSelf()

template<typename TInputImage, typename TOutput = double>

void itk::DiscreteGradientMagnitudeGaussianImageFunction< 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::LightObject.

◆ RecomputeGaussianKernel()

template<typename TInputImage, typename TOutput = double>

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

protected

Referenced by Initialize().

◆ SetInputImage()

template<typename TInputImage, typename TOutput = double>

void itk::DiscreteGradientMagnitudeGaussianImageFunction< 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, double, double >.

◆ SetInterpolationMode()

template<typename TInputImage, typename TOutput = double>

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

virtual

Set/Get the interpolation mode.

◆ SetMaximumError()

template<typename TInputImage, typename 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.

◆ SetMaximumKernelWidth()

template<typename TInputImage, typename 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.

◆ SetNormalizeAcrossScale()

template<typename TInputImage, typename 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.

◆ SetSigma()

template<typename TInputImage, typename 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 144 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

References SetVariance().

◆ SetUseImageSpacing()

template<typename TInputImage, typename TOutput = double>

virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< 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::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

References itk::FixedArray< double, Self::ImageDimension2 >::Length.

◆ SetVariance() [2/3]

template<typename TInputImage, typename TOutput = double>

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

inlinevirtual

Convenience method for setting the variance for all dimensions

Definition at line 134 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

References m_Variance, and itk::Object::Modified().

◆ SetVariance() [3/3]

template<typename TInputImage, typename 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

Referenced by SetSigma().

◆ UseImageSpacingOff()

template<typename TInputImage, typename TOutput = double>

virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::UseImageSpacingOff ( )

virtual

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

◆ UseImageSpacingOn()

template<typename TInputImage, typename TOutput = double>

virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< 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>

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

staticconstexpr

Dimension of the underlying image

Definition at line 77 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_InterpolationMode

template<typename TInputImage, typename TOutput = double>

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

private

Interpolation mode

Definition at line 249 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_KernelArray

template<typename TInputImage, typename TOutput = double>

KernelArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_KernelArray {}

private

Array of N-dimensional kernels used to calculate gradient components

Definition at line 237 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_MaximumError

template<typename TInputImage, typename TOutput = double>

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

private

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

Definition at line 224 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_MaximumKernelWidth

template<typename TInputImage, typename TOutput = double>

unsigned int itk::DiscreteGradientMagnitudeGaussianImageFunction< 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 229 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_NormalizeAcrossScale

template<typename TInputImage, typename TOutput = double>

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

private

Flag for scale-space normalization of derivatives

Definition at line 243 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_OperatorArray

template<typename TInputImage, typename TOutput = double>

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

private

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

Definition at line 234 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_OperatorImageFunction

template<typename TInputImage, typename TOutput = double>

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

private

OperatorImageFunction

Definition at line 240 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_UseImageSpacing

template<typename TInputImage, typename TOutput = double>

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

private

Flag to indicate whether to use image spacing

Definition at line 246 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

◆ m_Variance

template<typename TInputImage, typename TOutput = double>

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

private

Desired variance of the discrete Gaussian function

Definition at line 220 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.

Referenced by SetVariance().

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

itkDiscreteGradientMagnitudeGaussianImageFunction.h

Detailed Description

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

◆ KernelArrayType

◆ KernelType

◆ OperatorImageFunctionPointer

◆ OperatorImageFunctionType

◆ OrderArrayType

◆ Pointer

◆ Self

◆ Superclass

◆ VarianceArrayType

Constructor & Destructor Documentation

◆ DiscreteGradientMagnitudeGaussianImageFunction() [1/2]

◆ DiscreteGradientMagnitudeGaussianImageFunction() [2/2]

◆ ~DiscreteGradientMagnitudeGaussianImageFunction()

Member Function Documentation

◆ CreateAnother()

◆ Evaluate()

◆ EvaluateAtContinuousIndex()

◆ EvaluateAtIndex()

◆ GetInterpolationMode()

◆ GetMaximumError()

◆ GetMaximumKernelWidth()

◆ GetNameOfClass()

◆ GetNormalizeAcrossScale()

◆ GetUseImageSpacing()

◆ GetVariance()

◆ Initialize()

◆ New()

◆ NormalizeAcrossScaleOff()

◆ NormalizeAcrossScaleOn()

◆ operator=()

◆ PrintSelf()

◆ RecomputeGaussianKernel()

◆ SetInputImage()

◆ SetInterpolationMode()

◆ SetMaximumError()

◆ SetMaximumKernelWidth()

◆ SetNormalizeAcrossScale()

◆ SetSigma()

◆ SetUseImageSpacing()

◆ SetVariance() [1/3]

◆ SetVariance() [2/3]

◆ SetVariance() [3/3]

◆ UseImageSpacingOff()

◆ UseImageSpacingOn()

Member Data Documentation

◆ ImageDimension2

◆ m_InterpolationMode

◆ m_KernelArray

◆ m_MaximumError

◆ m_MaximumKernelWidth

◆ m_NormalizeAcrossScale

◆ m_OperatorArray

◆ m_OperatorImageFunction

◆ m_UseImageSpacing

◆ m_Variance