itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage > Class Template Reference

#include <itkDiscreteGaussianDerivativeImageFilter.h>

Inheritance diagram for itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >:

Collaboration diagram for itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >:

List of all members.

Public Types
typedef FixedArray< double, itkGetStaticConstMacro(ImageDimension) >	ArrayType
typedef SmartPointer< const Self >	ConstPointer
typedef TInputImage	InputImageType
typedef TInputImage::InternalPixelType	InputInternalPixelType
typedef TInputImage::PixelType	InputPixelType
typedef FixedArray< unsigned int, itkGetStaticConstMacro(ImageDimension) >	OrderArrayType
typedef TOutputImage	OutputImageType
typedef TOutputImage::InternalPixelType	OutputInternalPixelType
typedef TOutputImage::PixelType	OutputPixelType
typedef SmartPointer< Self >	Pointer
typedef DiscreteGaussianDerivativeImageFilter	Self
typedef ImageToImageFilter < TInputImage, TOutputImage >	Superclass
Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
virtual unsigned int	GetInternalNumberOfStreamDivisions () const
virtual const char *	GetNameOfClass () const
virtual void	SetInternalNumberOfStreamDivisions (unsigned int _arg)
	typedef (Concept::HasNumericTraits< OutputPixelType >) OutputHasNumericTraitsCheck
virtual void	SetOrder (OrderArrayType _arg)
virtual const OrderArrayType	GetOrder () const
virtual void	SetVariance (ArrayType _arg)
virtual const ArrayType	GetVariance () const
virtual void	SetMaximumError (ArrayType _arg)
virtual const ArrayType	GetMaximumError () const
virtual int	GetMaximumKernelWidth () const
virtual void	SetMaximumKernelWidth (int _arg)
void	SetOrder (const typename OrderArrayType::ValueType v)
void	SetVariance (const typename ArrayType::ValueType v)
void	SetMaximumError (const typename ArrayType::ValueType v)
virtual void	SetUseImageSpacing (bool _arg)
virtual bool	GetUseImageSpacing () const
virtual void	UseImageSpacingOn ()
virtual void	UseImageSpacingOff ()
virtual void	SetNormalizeAcrossScale (bool _arg)
virtual bool	GetNormalizeAcrossScale () const
virtual void	NormalizeAcrossScaleOn ()
virtual void	NormalizeAcrossScaleOff ()
Static Public Member Functions
static Pointer	New ()
Static Public Attributes
static const unsigned int	ImageDimension = TOutputImage::ImageDimension
Protected Member Functions
	DiscreteGaussianDerivativeImageFilter ()
void	GenerateData ()
virtual void	GenerateInputRequestedRegion () throw ( InvalidRequestedRegionError )
void	PrintSelf (std::ostream &os, Indent indent) const
virtual	~DiscreteGaussianDerivativeImageFilter ()
Private Member Functions
	DiscreteGaussianDerivativeImageFilter (const Self &)
void	operator= (const Self &)
Private Attributes
unsigned int	m_InternalNumberOfStreamDivisions
ArrayType	m_MaximumError
int	m_MaximumKernelWidth
bool	m_NormalizeAcrossScale
OrderArrayType	m_Order
bool	m_UseImageSpacing
ArrayType	m_Variance

---

Detailed Description

template<class TInputImage, class TOutputImage>
class itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >

Calculates image derivatives using discrete derivative gaussian kernels. This filter calculates Gaussian derivative by separable convolution of an image and a discrete Gaussian derivative operator (kernel).

The Gaussian operators used here were described by Tony Lindeberg (Discrete Scale-Space Theory and the Scale-Space Primal Sketch. Dissertation. Royal Institute of Technology, Stockholm, Sweden. May 1991.)

The variance or standard deviation (sigma) will be evaluated as pixel units if SetUseImageSpacing is off (false) or as physical units if SetUseImageSpacing is on (true, default). The variance can be set independently in each dimension.

When the Gaussian kernel is small, this filter tends to run faster than itk::RecursiveGaussianImageFilter.

Author:

Ivan Macia, VICOMTech, Spain, http://www.vicomtech.es

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

See also:

GaussianDerivativeOperator

Image

Neighborhood

NeighborhoodOperator

Definition at line 60 of file itkDiscreteGaussianDerivativeImageFilter.h.

---

Member Typedef Documentation

template<class TInputImage , class TOutputImage >

typedef FixedArray< double, itkGetStaticConstMacro(ImageDimension) > itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::ArrayType

Typedef of double containers

Definition at line 93 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef SmartPointer< const Self > itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::ConstPointer

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

Definition at line 68 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef TInputImage itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::InputImageType

Image type information.

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

Definition at line 74 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef TInputImage::InternalPixelType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::InputInternalPixelType

Definition at line 85 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef TInputImage::PixelType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::InputPixelType

Definition at line 84 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef FixedArray< unsigned int, itkGetStaticConstMacro(ImageDimension) > itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::OrderArrayType

Array for storing desired order of derivatives

Definition at line 96 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef TOutputImage itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::OutputImageType

Some convenient typedefs.

Reimplemented from itk::ImageSource< TOutputImage >.

Definition at line 78 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef TOutputImage::InternalPixelType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::OutputInternalPixelType

Definition at line 83 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef TOutputImage::PixelType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::OutputPixelType

Extract some information from the image types. Dimensionality of the two images is assumed to be the same.

Definition at line 82 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef SmartPointer< Self > itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::Pointer

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

Definition at line 67 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef DiscreteGaussianDerivativeImageFilter itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::Self

Standard class typedefs.

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

Definition at line 65 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

typedef ImageToImageFilter< TInputImage, TOutputImage > itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::Superclass

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

Definition at line 66 of file itkDiscreteGaussianDerivativeImageFilter.h.

---

Constructor & Destructor Documentation

template<class TInputImage , class TOutputImage >

itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::DiscreteGaussianDerivativeImageFilter

(

)

[inline, protected]

End concept checking

Definition at line 194 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

virtual itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::~DiscreteGaussianDerivativeImageFilter

(

)

[inline, protected, virtual]

Definition at line 205 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::DiscreteGaussianDerivativeImageFilter

(

const Self &

)

[private]

---

Member Function Documentation

template<class TInputImage , class TOutputImage >

virtual::itk::LightObject::Pointer itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::CreateAnother

(

void

)

const [virtual]

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::Object.

template<class TInputImage , class TOutputImage >

void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GenerateData

(

)

[protected, virtual]

Standard pipeline method. While this class does not implement a ThreadedGenerateData(), its GenerateData() delegates all calculations to an NeighborhoodOperatorImageFilter. Since the NeighborhoodOperatorImageFilter is multithreaded, this filter is multithreaded by default.

Reimplemented from itk::ImageSource< TOutputImage >.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GenerateInputRequestedRegion

(

)

throw ( InvalidRequestedRegionError ) [protected, virtual]

DiscreteGaussianDerivativeImageFilter needs a larger input requested region than the output requested region (larger by the size of the Gaussian kernel). As such, DiscreteGaussianDerivativeImageFilter needs to provide an implementation for GenerateInputRequestedRegion() in order to inform the pipeline execution model.

See also:

ImageToImageFilter::GenerateInputRequestedRegion()

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

template<class TInputImage , class TOutputImage >

virtual unsigned int itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GetInternalNumberOfStreamDivisions

(

)

const [virtual]

template<class TInputImage , class TOutputImage >

virtual const ArrayType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GetMaximumError

(

)

const [virtual]

The algorithm will size the discrete kernel so that the error resulting from truncation of the kernel is no greater than MaximumError. The default is 0.01 in each dimension.

template<class TInputImage , class TOutputImage >

virtual int itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GetMaximumKernelWidth

(

)

const [virtual]

Set the kernel to be no wider than MaximumKernelWidth pixels, even if MaximumError demands it. The default is 32 pixels.

template<class TInputImage , class TOutputImage >

virtual const char* itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GetNameOfClass

(

)

const [virtual]

Run-time type information (and related methods).

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

template<class TInputImage , class TOutputImage >

virtual bool itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GetNormalizeAcrossScale

(

)

const [virtual]

Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.

template<class TInputImage , class TOutputImage >

virtual const OrderArrayType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GetOrder

(

)

const [virtual]

Order of derivatives in each dimension. Sets the derivative order independently for each dimension, but see also SetOrder(const unsigned int v). The default is 1 in each dimension.

template<class TInputImage , class TOutputImage >

virtual bool itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GetUseImageSpacing

(

)

const [virtual]

Set/Get whether or not the filter will use the spacing of the input image in its calculations. Default is ImageSpacingOn.

template<class TInputImage , class TOutputImage >

virtual const ArrayType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::GetVariance

(

)

const [virtual]

The variance for the discrete Gaussian kernel. Sets the variance independently for each dimension, but see also SetVariance(const double v). The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels.

template<class TInputImage , class TOutputImage >

static Pointer itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::New

(

)

[static]

Method for creation through the object factory.

Reimplemented from itk::Object.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::NormalizeAcrossScaleOff

(

)

[virtual]

Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::NormalizeAcrossScaleOn

(

)

[virtual]

Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.

template<class TInputImage , class TOutputImage >

void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::operator=

(

const Self &

)

[private]

PushBackInput(), PushFronInput() in the public section force the input to be the type expected by an ImageToImageFilter. However, these methods end of "hiding" the versions from the superclass (ProcessObject) whose arguments are DataObjects. Here, we re-expose the versions from ProcessObject to avoid warnings about hiding methods from the superclass.

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

template<class TInputImage , class TOutputImage >

void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const [protected, virtual]

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetInternalNumberOfStreamDivisions

(

unsigned int

_arg

)

[virtual]

Set/Get number of pieces to divide the input for the internal composite pipeline. The upstream pipeline will not be effected.

The default value is $ImageDimension^2$.

This parameter was introduced to reduce the memory used by images internally, at the cost of performance.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetMaximumError

(

ArrayType

_arg

)

[virtual]

The algorithm will size the discrete kernel so that the error resulting from truncation of the kernel is no greater than MaximumError. The default is 0.01 in each dimension.

template<class TInputImage , class TOutputImage >

void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetMaximumError

(

const typename ArrayType::ValueType

v

)

[inline]

Convenience Set methods for setting all dimensional parameters to the same values.

Definition at line 160 of file itkDiscreteGaussianDerivativeImageFilter.h.

References itk::FixedArray< TValueType, VLength >::Fill().

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetMaximumKernelWidth

(

int

_arg

)

[virtual]

Set the kernel to be no wider than MaximumKernelWidth pixels, even if MaximumError demands it. The default is 32 pixels.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetNormalizeAcrossScale

(

bool

_arg

)

[virtual]

Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetOrder

(

OrderArrayType

_arg

)

[virtual]

Order of derivatives in each dimension. Sets the derivative order independently for each dimension, but see also SetOrder(const unsigned int v). The default is 1 in each dimension.

template<class TInputImage , class TOutputImage >

void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetOrder

(

const typename OrderArrayType::ValueType

v

)

[inline]

Convenience Set methods for setting all dimensional parameters to the same values.

Definition at line 144 of file itkDiscreteGaussianDerivativeImageFilter.h.

References itk::FixedArray< TValueType, VLength >::Fill().

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetUseImageSpacing

(

bool

_arg

)

[virtual]

Set/Get whether or not the filter will use the spacing of the input image in its calculations. Default is ImageSpacingOn.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetVariance

(

ArrayType

_arg

)

[virtual]

The variance for the discrete Gaussian kernel. Sets the variance independently for each dimension, but see also SetVariance(const double v). The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels.

template<class TInputImage , class TOutputImage >

void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::SetVariance

(

const typename ArrayType::ValueType

v

)

[inline]

Convenience Set methods for setting all dimensional parameters to the same values.

Definition at line 152 of file itkDiscreteGaussianDerivativeImageFilter.h.

References itk::FixedArray< TValueType, VLength >::Fill().

template<class TInputImage , class TOutputImage >

itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::typedef

(

Concept::HasNumericTraits< OutputPixelType >

)

Begin concept checking This class requires OutputHasNumericTraitsCheck in the form of ( Concept::HasNumericTraits< OutputPixelType > )

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::UseImageSpacingOff

(

)

[virtual]

Set/Get whether or not the filter will use the spacing of the input image in its calculations. Default is ImageSpacingOn.

template<class TInputImage , class TOutputImage >

virtual void itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::UseImageSpacingOn

(

)

[virtual]

Set/Get whether or not the filter will use the spacing of the input image in its calculations. Default is ImageSpacingOn.

---

Member Data Documentation

template<class TInputImage , class TOutputImage >

const unsigned int itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::ImageDimension = TOutputImage::ImageDimension [static]

Extract some information from the image types. Dimensionality of the two images is assumed to be the same.

Definition at line 90 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

unsigned int itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::m_InternalNumberOfStreamDivisions [private]

Number of pieces to divide the input on the internal composite pipeline. The upstream pipeline will not be effected.

Definition at line 255 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

ArrayType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::m_MaximumError [private]

The maximum error of the gaussian blurring kernel in each dimensional direction. For definition of maximum error, see GaussianOperator.

See also:

GaussianOperator

Definition at line 241 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

int itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::m_MaximumKernelWidth [private]

Maximum allowed kernel width for any dimension of the discrete Gaussian approximation

Definition at line 245 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

bool itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::m_NormalizeAcrossScale [private]

Flag for scale-space normalization of derivatives.

Definition at line 251 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

OrderArrayType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::m_Order [private]

The order of the derivatives in each dimensional direction.

Definition at line 232 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

bool itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::m_UseImageSpacing [private]

Flag to indicate whether to use image spacing

Definition at line 248 of file itkDiscreteGaussianDerivativeImageFilter.h.

template<class TInputImage , class TOutputImage >

ArrayType itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >::m_Variance [private]

The variance of the gaussian blurring kernel in each dimensional direction.

Definition at line 236 of file itkDiscreteGaussianDerivativeImageFilter.h.

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

• itkDiscreteGaussianDerivativeImageFilter.h