itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage > Class Template Reference
[Image Enhancement Filters, Image Feature Extraction Filters]

Blurs an image by separable convolution with discrete gaussian kernels. This filter performs Gaussian blurring by separable convolution of an image and a discrete Gaussian operator (kernel). More...

#include <itkDiscreteGaussianImageFilter.h>

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

[legend]Collaboration diagram for itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >:

[legend]List of all members.

Public Types
typedef DiscreteGaussianImageFilter	Self
typedef ImageToImageFilter< TInputImage, TOutputImage >	Superclass
typedef SmartPointer< Self >	Pointer
typedef SmartPointer< const Self >	ConstPointer
typedef TInputImage	InputImageType
typedef TOutputImage	OutputImageType
typedef TOutputImage::PixelType	OutputPixelType
typedef TOutputImage::InternalPixelType	OutputInternalPixelType
typedef TInputImage::PixelType	InputPixelType
typedef TInputImage::InternalPixelType	InputInternalPixelType
Public Member Functions
virtual const char *	GetClassName () const
	itkStaticConstMacro (ImageDimension, unsigned int, TOutputImage::ImageDimension)
virtual unsigned int	GetFilterDimensionality ()
virtual void	SetFilterDimensionality (unsigned int _arg)
void	SetUseImageSpacingOn ()
void	SetUseImageSpacingOff ()
virtual void	GenerateInputRequestedRegion () throw (InvalidRequestedRegionError)
virtual void	SetVariance (double data[])
virtual void	SetVariance (float data[])
virtual const double *	GetVariance () const
virtual void	SetMaximumError (double data[])
virtual void	SetMaximumError (float data[])
virtual const double *	GetMaximumError () const
virtual int	GetMaximumKernelWidth ()
virtual void	SetMaximumKernelWidth (int _arg)
void	SetVariance (const double v)
void	SetMaximumError (const double v)
void	SetVariance (const float v)
void	SetMaximumError (const float v)
virtual void	SetUseImageSpacing (bool _arg)
virtual bool	GetUseImageSpacing ()
Static Public Member Functions
Pointer	New ()
Protected Member Functions
	DiscreteGaussianImageFilter ()
virtual	~DiscreteGaussianImageFilter ()
void	PrintSelf (std::ostream &os, Indent indent) const
void	GenerateData ()

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Detailed Description

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

Blurs an image by separable convolution with discrete gaussian kernels. This filter performs Gaussian blurring by separable convolution of an image and a discrete Gaussian operator (kernel).

The Gaussian operator used here was described by Tony Lindeberg (Discrete Scale-Space Theory and the Scale-Space Primal Sketch. Dissertation. Royal Institute of Technology, Stockholm, Sweden. May 1991.) The Gaussian kernel used here was designed so that smoothing and derivative operations commute after discretization.

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.

See also:

GaussianOperator

Image

Neighborhood

NeighborhoodOperator

Definition at line 55 of file itkDiscreteGaussianImageFilter.h.

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Member Typedef Documentation

template<class TInputImage, class TOutputImage> typedef SmartPointer<const Self> itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::ConstPointer

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >. Definition at line 63 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef TInputImage itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::InputImageType

Image type information. Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >. Definition at line 72 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef TInputImage::InternalPixelType itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::InputInternalPixelType

Definition at line 80 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef TInputImage::PixelType itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::InputPixelType

Definition at line 79 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef TOutputImage itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::OutputImageType

Some convenient typedefs. Reimplemented from itk::ImageSource< TOutputImage >. Definition at line 73 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef TOutputImage::InternalPixelType itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::OutputInternalPixelType

Definition at line 78 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef TOutputImage::PixelType itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::OutputPixelType

Extract some information from the image types. Dimensionality of the two images is assumed to be the same. Definition at line 77 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef SmartPointer<Self> itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::Pointer

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >. Definition at line 62 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef DiscreteGaussianImageFilter itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::Self

Standard class typedefs. Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >. Definition at line 60 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> typedef ImageToImageFilter< TInputImage, TOutputImage > itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::Superclass

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >. Definition at line 61 of file itkDiscreteGaussianImageFilter.h.

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Constructor & Destructor Documentation

template<class TInputImage, class TOutputImage> itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::DiscreteGaussianImageFilter (   )  [inline, protected]

Definition at line 172 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> virtual itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::~DiscreteGaussianImageFilter (   )  [inline, protected, virtual]

Definition at line 184 of file itkDiscreteGaussianImageFilter.h.

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Member Function Documentation

template<class TInputImage, class TOutputImage> void itk::DiscreteGaussianImageFilter< 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::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::GenerateInputRequestedRegion (   )  throw (InvalidRequestedRegionError) [virtual]

DiscreteGaussianImageFilter needs a larger input requested region than the output requested region (larger by the size of the Gaussian kernel). As such, DiscreteGaussianImageFilter 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 const char* itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::GetClassName (   )  const [virtual]

Run-time type information (and related methods). Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

template<class TInputImage, class TOutputImage> virtual unsigned int itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::GetFilterDimensionality (   )  [virtual]

template<class TInputImage, class TOutputImage> virtual const double* itk::DiscreteGaussianImageFilter< 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::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::GetMaximumKernelWidth (   )  [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 bool itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::GetUseImageSpacing (   )  [virtual]

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

template<class TInputImage, class TOutputImage> virtual const double* itk::DiscreteGaussianImageFilter< 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> itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::itkStaticConstMacro (  ImageDimension  , unsigned  int, TOutputImage::ImageDimension  )

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

template<class TInputImage, class TOutputImage> Pointer itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::New (   )  [static]

Method for creation through the object factory. Reimplemented from itk::Object.

template<class TInputImage, class TOutputImage> void itk::DiscreteGaussianImageFilter< 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::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetFilterDimensionality (  unsigned int  _arg  )  [virtual]

template<class TInputImage, class TOutputImage> void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetMaximumError (  const float  v  )  [inline]

Convenience get/set methods for setting all dimensional parameters to the same values. Definition at line 138 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetMaximumError (  const double  v  )  [inline]

Convenience get/set methods for setting all dimensional parameters to the same values. Definition at line 122 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> virtual void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetMaximumError (  float  data[]  )  [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 void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetMaximumError (  double  data[]  )  [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 void itk::DiscreteGaussianImageFilter< 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::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetUseImageSpacing (  bool  _arg  )  [virtual]

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

template<class TInputImage, class TOutputImage> void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetUseImageSpacingOff (   )  [inline]

Ignore the image spacing. Use this option if you want to specify Gaussian variance in pixels. Default is ImageSpacingOn. Definition at line 154 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetUseImageSpacingOn (   )  [inline]

Use the image spacing information in calculations. Use this option if you want to specify Gaussian variance in real world units. Default is ImageSpacingOn. Definition at line 149 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetVariance (  const float  v  )  [inline]

Convenience get/set methods for setting all dimensional parameters to the same values. Definition at line 132 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetVariance (  const double  v  )  [inline]

Convenience get/set methods for setting all dimensional parameters to the same values. Definition at line 116 of file itkDiscreteGaussianImageFilter.h.

template<class TInputImage, class TOutputImage> virtual void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetVariance (  float  data[]  )  [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> virtual void itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >::SetVariance (  double  data[]  )  [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.

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

• itkDiscreteGaussianImageFilter.h

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