ITK  5.2.0
Insight Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Static Public Attributes | List of all members
itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput > Class Template Reference

#include <itkDiscreteGaussianDerivativeImageFunction.h>

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

Public Types

using ConstPointer = SmartPointer< const Self >
 
using ContinuousIndexType = typename Superclass::ContinuousIndexType
 
using GaussianDerivativeOperatorArrayType = FixedArray< GaussianDerivativeOperatorType, Self::ImageDimension2 >
 
using GaussianDerivativeOperatorType = itk::GaussianDerivativeOperator< TOutput, Self::ImageDimension2 >
 
using IndexType = typename Superclass::IndexType
 
using IndexValueType = typename Superclass::IndexValueType
 
using InputImageType = typename Superclass::InputImageType
 
using InputPixelType = typename Superclass::InputPixelType
 
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 OutputType = typename Superclass::OutputType
 
using Pointer = SmartPointer< Self >
 
using PointType = typename Superclass::PointType
 
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

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
 
virtual const char * GetNameOfClass () const
 
- Public Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
TOutput Evaluate (const PointType &point) const override=0
 
virtual TOutput EvaluateAtContinuousIndex (const ContinuousIndexType &index) const=0
 
virtual TOutput EvaluateAtIndex (const IndexType &index) const=0
 
const InputImageTypeGetInputImage () const
 
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
 
void ConvertPointToNearestIndex (const PointType &point, IndexType &index) const
 
void ConvertPointToContinuousIndex (const PointType &point, ContinuousIndexType &cindex) const
 
void ConvertContinuousIndexToNearestIndex (const ContinuousIndexType &cindex, IndexType &index) const
 
virtual const IndexTypeGetStartIndex () const
 
virtual const IndexTypeGetEndIndex () const
 
virtual const ContinuousIndexTypeGetStartContinuousIndex () const
 
virtual const ContinuousIndexTypeGetEndContinuousIndex () 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
 
virtual void DebugOff () const
 
virtual void DebugOn () const
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary ()
 
const MetaDataDictionaryGetMetaDataDictionary () const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () 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
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
 itkCloneMacro (Self)
 
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 flag)
 
- 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
 
VarianceArrayType m_Variance
 
OrderArrayType m_Order
 
double m_MaximumError { 0.005 }
 
unsigned int m_MaximumKernelWidth { 30 }
 
GaussianDerivativeOperatorArrayType m_OperatorArray
 
KernelType m_DerivativeKernel
 
OperatorImageFunctionPointer m_OperatorImageFunction
 
bool m_NormalizeAcrossScale { true }
 
bool m_UseImageSpacing { true }
 
InterpolationModeEnum m_InterpolationMode { InterpolationModeEnum::NearestNeighbourInterpolation }
 
virtual void SetVariance (VarianceArrayType _arg)
 
virtual const VarianceArrayType GetVariance () const
 
virtual void SetVariance (double data[])
 
virtual void SetVariance (double variance)
 
void SetSigma (const double sigma)
 
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 (const InterpolationModeEnum _arg)
 
virtual InterpolationModeEnum GetInterpolationMode () const
 
void SetInputImage (const InputImageType *ptr) override
 
virtual void Initialize ()
 
 DiscreteGaussianDerivativeImageFunction ()
 
 DiscreteGaussianDerivativeImageFunction (const Self &)
 
 ~DiscreteGaussianDerivativeImageFunction () override=default
 
void operator= (const Self &)
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
void RecomputeGaussianKernel ()
 

Additional Inherited Members

- Protected Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
 ImageFunction ()
 
 ~ImageFunction () override=default
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
- 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 ()
 
 ~Object () override
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
- 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 ()
 
- Protected Attributes inherited from itk::ImageFunction< TInputImage, TOutput, TOutput >
InputImageConstPointer m_Image
 
IndexType m_StartIndex
 
IndexType m_EndIndex
 
ContinuousIndexType m_StartContinuousIndex
 
ContinuousIndexType m_EndContinuousIndex
 
- Protected Attributes inherited from itk::LightObject
std::atomic< int > m_ReferenceCount
 

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, http://www.vicomtech.es

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

See also
NeighborhoodOperator
ImageFunction

Definition at line 47 of file itkDiscreteGaussianDerivativeImageFunction.h.

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.

◆ ContinuousIndexType

template<typename TInputImage , typename TOutput = double>
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::ContinuousIndexType = typename Superclass::ContinuousIndexType

Definition at line 72 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.

◆ IndexType

template<typename TInputImage , typename TOutput = double>
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::IndexType = typename Superclass::IndexType

Definition at line 70 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ IndexValueType

template<typename TInputImage , typename TOutput = double>
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::IndexValueType = typename Superclass::IndexValueType

Definition at line 71 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ InputImageType

template<typename TInputImage , typename TOutput = double>
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::InputImageType = typename Superclass::InputImageType

Image dependent types.

Definition at line 68 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ InputPixelType

template<typename TInputImage , typename TOutput = double>
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::InputPixelType = typename Superclass::InputPixelType

Definition at line 69 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.

◆ OutputType

template<typename TInputImage , typename TOutput = double>
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OutputType = typename Superclass::OutputType

Output type.

Definition at line 79 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.

◆ PointType

template<typename TInputImage , typename TOutput = double>
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::PointType = typename Superclass::PointType

Definition at line 73 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

Desired variance of the discrete Gaussian function.

◆ DiscreteGaussianDerivativeImageFunction() [2/2]

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

Desired variance of the discrete Gaussian function.

Definition at line 218 of file itkDiscreteGaussianDerivativeImageFunction.h.

◆ ~DiscreteGaussianDerivativeImageFunction()

template<typename TInputImage , typename TOutput = double>
itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::~DiscreteGaussianDerivativeImageFunction ( )
overrideprotecteddefault

Desired variance of the discrete Gaussian function.

Member Function Documentation

◆ CreateAnother()

template<typename TInputImage , typename TOutput = double>
virtual::itk::LightObject::Pointer itk::DiscreteGaussianDerivativeImageFunction< 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::Object.

◆ Evaluate()

template<typename TInputImage , typename TOutput = double>
OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Evaluate ( const PointType point) const
override

Evaluate the function at specified point.

◆ EvaluateAtContinuousIndex()

template<typename TInputImage , typename TOutput = double>
OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::EvaluateAtContinuousIndex ( const ContinuousIndexType index) const
override

Evaluate the function at specified ContinuousIndex position.

◆ EvaluateAtIndex()

template<typename TInputImage , typename TOutput = double>
OutputType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::EvaluateAtIndex ( const IndexType index) const
override

Evaluate the function at specified Index position

◆ GetInterpolationMode()

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

Desired variance of the discrete Gaussian function.

◆ GetMaximumError()

template<typename TInputImage , typename TOutput = double>
virtual double itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetMaximumError ( ) const
virtual

Desired variance of the discrete Gaussian function.

◆ GetMaximumKernelWidth()

template<typename TInputImage , typename TOutput = double>
virtual unsigned int itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetMaximumKernelWidth ( ) const
virtual

Desired variance of the discrete Gaussian function.

◆ GetNameOfClass()

template<typename TInputImage , typename 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 >.

◆ GetNormalizeAcrossScale()

template<typename TInputImage , typename TOutput = double>
virtual bool itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetNormalizeAcrossScale ( ) const
virtual

Desired variance of the discrete Gaussian function.

◆ GetOrder()

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

Desired variance of the discrete Gaussian function.

◆ GetUseImageSpacing()

template<typename TInputImage , typename TOutput = double>
virtual bool itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetUseImageSpacing ( ) const
virtual

Desired variance of the discrete Gaussian function.

◆ GetVariance()

template<typename TInputImage , typename TOutput = double>
virtual const VarianceArrayType itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GetVariance ( ) const
virtual

Desired variance of the discrete Gaussian function.

◆ 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.

◆ NormalizeAcrossScaleOff()

template<typename TInputImage , typename TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::NormalizeAcrossScaleOff ( )
virtual

Desired variance of the discrete Gaussian function.

◆ NormalizeAcrossScaleOn()

template<typename TInputImage , typename TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::NormalizeAcrossScaleOn ( )
virtual

Desired variance of the discrete Gaussian function.

◆ operator=()

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

Desired variance of the discrete Gaussian function.

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

Desired variance of the discrete Gaussian function.

Reimplemented from itk::Object.

◆ RecomputeGaussianKernel()

template<typename TInputImage , typename TOutput = double>
void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::RecomputeGaussianKernel ( )
protected

Desired variance of the discrete Gaussian function.

◆ SetInputImage()

template<typename TInputImage , typename TOutput = double>
void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::SetInputImage ( const InputImageType ptr)
override

Set the input image.

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

◆ 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

Desired variance of the discrete Gaussian function.

◆ 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

Desired variance of the discrete Gaussian function.

◆ 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.

◆ UseImageSpacingOff()

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

Desired variance of the discrete Gaussian function.

◆ UseImageSpacingOn()

template<typename TInputImage , typename TOutput = double>
virtual void itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::UseImageSpacingOn ( )
virtual

Desired variance of the discrete Gaussian function.

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: