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itk::MRFImageFilter< TInputImage, TClassifiedImage > Class Template Reference
[Markov Random Field-based Filters]

Implementation of a labeller object that uses Markov Random Fields to classify pixels in an image data set. More...

#include <itkMRFImageFilter.h>

Inheritance diagram for itk::MRFImageFilter< TInputImage, TClassifiedImage >:
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Collaboration diagram for itk::MRFImageFilter< TInputImage, TClassifiedImage >:
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List of all members.

Public Types

typedef ImageClassifierBase
< TInputImage,
TClassifiedImage > 
ClassifierType
typedef SmartPointer< const SelfConstPointer
typedef DataObject::Pointer DataObjectPointer
typedef std::vector
< DataObjectPointer
DataObjectPointerArray
typedef
DataObjectPointerArray::size_type 
DataObjectPointerArraySizeType
typedef
LabelledImageIndexType::IndexValueType 
IndexValueType
typedef TInputImage::ConstPointer InputImageConstPointer
typedef
InputImageFaceListType::iterator 
InputImageFaceListIterator
typedef
InputImageFacesCalculator::FaceListType 
InputImageFaceListType
typedef
NeighborhoodAlgorithm::ImageBoundaryFacesCalculator
< TInputImage > 
InputImageFacesCalculator
typedef
ConstNeighborhoodIterator
< TInputImage > 
InputImageNeighborhoodIterator
typedef
InputImageNeighborhoodIterator::RadiusType 
InputImageNeighborhoodRadiusType
typedef TInputImage::PixelType InputImagePixelType
typedef TInputImage::Pointer InputImagePointer
typedef
ImageRegionConstIterator
< TInputImage > 
InputImageRegionConstIterator
typedef ImageRegionIterator
< TInputImage > 
InputImageRegionIterator
typedef TInputImage::RegionType InputImageRegionType
typedef TInputImage InputImageType
typedef
LabelledImageFaceListType::iterator 
LabelledImageFaceListIterator
typedef
LabelledImageFacesCalculator::FaceListType 
LabelledImageFaceListType
typedef
NeighborhoodAlgorithm::ImageBoundaryFacesCalculator
< TClassifiedImage > 
LabelledImageFacesCalculator
typedef TClassifiedImage::IndexType LabelledImageIndexType
typedef NeighborhoodIterator
< TClassifiedImage > 
LabelledImageNeighborhoodIterator
typedef
LabelledImageNeighborhoodIterator::RadiusType 
LabelledImageNeighborhoodRadiusType
typedef
TClassifiedImage::OffsetType 
LabelledImageOffsetType
typedef TClassifiedImage::PixelType LabelledImagePixelType
typedef TClassifiedImage::Pointer LabelledImagePointer
typedef ImageRegionIterator
< TClassifiedImage > 
LabelledImageRegionIterator
typedef
TClassifiedImage::RegionType 
LabelledImageRegionType
typedef TInputImage::SizeType NeighborhoodRadiusType
typedef
Superclass::OutputImagePixelType 
OutputImagePixelType
typedef
Superclass::OutputImagePointer 
OutputImagePointer
typedef
Superclass::OutputImageRegionType 
OutputImageRegionType
typedef TClassifiedImage OutputImageType
typedef SmartPointer< SelfPointer
typedef MRFImageFilter Self
typedef TInputImage::SizeType SizeType
enum  StopConditionType {
  MaximumNumberOfIterations = 1,
  ErrorTolerance
}
typedef ImageToImageFilter
< TInputImage,
TClassifiedImage > 
Superclass
typedef TClassifiedImage::PixelType TrainingImagePixelType
typedef TClassifiedImage::Pointer TrainingImagePointer

Public Member Functions

virtual void AbortGenerateDataOff ()
virtual void AbortGenerateDataOn ()
virtual LightObject::Pointer CreateAnother () const
virtual void DebugOff () const
virtual void DebugOn () const
virtual void Delete ()
virtual const bool & GetAbortGenerateData ()
CommandGetCommand (unsigned long tag)
bool GetDebug () const
DataObjectPointerArrayGetInputs ()
MetaDataDictionaryGetMetaDataDictionary (void)
const MetaDataDictionaryGetMetaDataDictionary (void) const
virtual unsigned long GetMTime () const
MultiThreaderGetMultiThreader ()
virtual const char * GetNameOfClass () const
const NeighborhoodRadiusType GetNeighborhoodRadius () const
DataObjectPointerArraySizeType GetNumberOfInputs () const
virtual const unsigned int & GetNumberOfIterations ()
virtual
DataObjectPointerArraySizeType 
GetNumberOfValidRequiredInputs () const
virtual const float & GetProgress ()
virtual int GetReferenceCount () const
virtual const StopConditionTypeGetStopCondition ()
virtual void GraftNthOutput (unsigned int idx, DataObject *output)
virtual void GraftOutput (DataObject *output)
bool HasObserver (const EventObject &event) const
void InvokeEvent (const EventObject &)
void InvokeEvent (const EventObject &) const
virtual DataObjectPointer MakeOutput (unsigned int idx)
virtual void Modified () const
virtual void PrepareOutputs ()
void Print (std::ostream &os, Indent indent=0) const
virtual void PropagateRequestedRegion (DataObject *output)
virtual void Register () const
void RemoveAllObservers ()
void RemoveObserver (unsigned long tag)
virtual void ResetPipeline ()
virtual void SetAbortGenerateData (bool _arg)
void SetClassifier (typename ClassifierType::Pointer ptrToClassifier)
void SetDebug (bool debugFlag) const
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
void SetNeighborhoodRadius (const unsigned long *radiusArray)
void SetNeighborhoodRadius (const unsigned long)
void SetNeighborhoodRadius (const NeighborhoodRadiusType &)
virtual void SetProgress (float _arg)
virtual void SetReferenceCount (int)
virtual void UnRegister () const
virtual void Update ()
virtual void UpdateLargestPossibleRegion ()
virtual void UpdateOutputData (DataObject *output)
virtual void UpdateOutputInformation ()
void UpdateProgress (float amount)

virtual void SetNumberOfClasses (unsigned int _arg)
virtual unsigned int GetNumberOfClasses () const

virtual void SetMaximumNumberOfIterations (unsigned int _arg)
virtual unsigned int GetMaximumNumberOfIterations () const

virtual void SetErrorTolerance (double _arg)
virtual double GetErrorTolerance () const

virtual void SetSmoothingFactor (double _arg)
virtual double GetSmoothingFactor () const

virtual void SetMRFNeighborhoodWeight (std::vector< double > BetaMatrix)
virtual std::vector< double > GetMRFNeighborhoodWeight ()

virtual void SetInput (const InputImageType *image)
virtual void SetInput (unsigned int, const TInputImage *image)
const InputImageTypeGetInput (void)
const InputImageTypeGetInput (unsigned int idx)

virtual void PushBackInput (const InputImageType *image)
virtual void PopBackInput ()
virtual void PushFrontInput (const InputImageType *image)
virtual void PopFrontInput ()

OutputImageTypeGetOutput (void)
OutputImageTypeGetOutput (unsigned int idx)

DataObjectPointerArrayGetOutputs ()
DataObjectPointerArraySizeType GetNumberOfOutputs () const

virtual void SetReleaseDataFlag (bool flag)
virtual bool GetReleaseDataFlag () const
void ReleaseDataFlagOn ()
void ReleaseDataFlagOff ()

virtual void SetReleaseDataBeforeUpdateFlag (bool _arg)
virtual const bool & GetReleaseDataBeforeUpdateFlag ()
virtual void ReleaseDataBeforeUpdateFlagOn ()
virtual void ReleaseDataBeforeUpdateFlagOff ()

virtual void SetNumberOfThreads (int _arg)
virtual const int & GetNumberOfThreads ()

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

Static Public Member Functions

static void BreakOnError ()
static Pointer New ()

static void SetGlobalWarningDisplay (bool flag)
static bool GetGlobalWarningDisplay ()
static void GlobalWarningDisplayOn ()
static void GlobalWarningDisplayOff ()

Static Public Attributes

static const unsigned int ClassifiedImageDimension = TClassifiedImage::ImageDimension
static const unsigned int InputImageDimension = TInputImage::ImageDimension

static const unsigned int OutputImageDimension

Protected Types

typedef
ImageToImageFilterDetail::ImageRegionCopier
< itkGetStaticConstMacro(OutputImageDimension),
itkGetStaticConstMacro(InputImageDimension)> 
InputToOutputRegionCopierType
typedef ImageRegionIterator
< LabelStatusImageType
LabelStatusImageIterator
typedef NeighborhoodIterator
< LabelStatusImageType
LabelStatusImageNeighborhoodIterator
typedef
LabelStatusImageType::Pointer 
LabelStatusImagePointer
typedef Image< int,
itkGetStaticConstMacro(InputImageDimension) > 
LabelStatusImageType
typedef
LabelStatusImageType::IndexType 
LabelStatusIndexType
typedef
LabelStatusImageType::RegionType 
LabelStatusRegionType
typedef
ImageToImageFilterDetail::ImageRegionCopier
< itkGetStaticConstMacro(InputImageDimension),
itkGetStaticConstMacro(OutputImageDimension)> 
OutputToInputRegionCopierType

typedef int InternalReferenceCountType

Protected Member Functions

virtual void AfterThreadedGenerateData ()
void Allocate ()
virtual void AllocateOutputs ()
virtual void ApplyMRFImageFilter ()
virtual void BeforeThreadedGenerateData ()
virtual void CacheInputReleaseDataFlags ()
virtual void CallCopyInputRegionToOutputRegion (OutputImageRegionType &destRegion, const InputImageRegionType &srcRegion)
virtual void CallCopyOutputRegionToInputRegion (InputImageRegionType &destRegion, const OutputImageRegionType &srcRegion)
virtual void DoNeighborhoodOperation (const InputImageNeighborhoodIterator &imageIter, LabelledImageNeighborhoodIterator &labelledIter, LabelStatusImageNeighborhoodIterator &labelStatusIter)
virtual void EnlargeOutputRequestedRegion (DataObject *)
virtual void GenerateData ()
virtual void GenerateInputRequestedRegion ()
virtual void GenerateOutputInformation ()
virtual void GenerateOutputRequestedRegion (DataObject *output)
virtual void MinimizeFunctional ()
 MRFImageFilter ()
bool PrintObservers (std::ostream &os, Indent indent) const
void PrintSelf (std::ostream &os, Indent indent) const
virtual void PropagateResetPipeline ()
virtual void ReleaseInputs ()
virtual void RestoreInputReleaseDataFlags ()
void SetNumberOfInputs (unsigned int num)
void SetNumberOfOutputs (unsigned int num)
virtual int SplitRequestedRegion (int i, int num, OutputImageRegionType &splitRegion)
virtual void ThreadedGenerateData (const OutputImageRegionType &outputRegionForThread, int threadId) ITK_NO_RETURN
 ~MRFImageFilter ()

const DataObjectGetInput (unsigned int idx) const

void PushBackInput (const DataObject *input)
void PushFrontInput (const DataObject *input)

const DataObjectGetOutput (unsigned int idx) const

virtual void SetNthInput (unsigned int num, DataObject *input)
virtual void AddInput (DataObject *input)
virtual void RemoveInput (DataObject *input)
virtual void SetNumberOfRequiredInputs (unsigned int _arg)
virtual const unsigned int & GetNumberOfRequiredInputs ()

virtual void SetNthOutput (unsigned int num, DataObject *output)
virtual void AddOutput (DataObject *output)
virtual void RemoveOutput (DataObject *output)
virtual void SetNumberOfRequiredOutputs (unsigned int _arg)
virtual const unsigned int & GetNumberOfRequiredOutputs ()

virtual void PrintHeader (std::ostream &os, Indent indent) const
virtual void PrintTrailer (std::ostream &os, Indent indent) const

Static Protected Member Functions

static ITK_THREAD_RETURN_TYPE ThreaderCallback (void *arg)

Protected Attributes

TimeStamp m_OutputInformationMTime
InternalReferenceCountType m_ReferenceCount
SimpleFastMutexLock m_ReferenceCountLock
bool m_Updating

Detailed Description

template<class TInputImage, class TClassifiedImage>
class itk::MRFImageFilter< TInputImage, TClassifiedImage >

Implementation of a labeller object that uses Markov Random Fields to classify pixels in an image data set.

This object classifies pixels based on a Markov Random Field (MRF) model.This implementation uses the maximum a posteriori (MAP) estimates for modeling the MRF. The object traverses the data set and uses the model generated by the Mahalanobis distance classifier to gets the the distance between each pixel in the data set to a set of known classes, updates the distances by evaluating the influence of its neighboring pixels (based on a MRF model) and finally, classifies each pixel to the class which has the minimum distance to that pixel (taking the neighborhood influence under consideration). DoNeighborhoodOperation is the function that can be modified to achieve different falvors of MRF filters in derived classes.

The a classified initial labeled image is needed. It is important that the number of expected classes be set before calling the classifier. In our case we have used the ImageClassifer using a Gaussian model to generate the initial labels. This classifier requires the user to ensure that an appropriate membership functions be provided. See the documentation of the image classifier class for more information.

The influence of a neighborhood on a given pixel's classification (the MRF term) is computed by calculating a weighted sum of number of class labels in a three dimensional neighborhood. The basic idea of this neighborhood influence is that if a large number of neighbors of a pixel are of one class, then the current pixel is likely to be of the same class.

The dimensions of the neighborhood is same as the input image dimension and values of the weighting parameters are either specified by the user through the beta matrix parameter. The default weighting table is generated during object construction. The following table shows an example of a 3x3x3 neighborhood and the weighting values used. A 3 x 3 x 3 kernel is used where each value is a nonnegative parameter, which encourages neighbors to be of the same class. In this example, the influence of the pixels in the same slice is assigned a weight 1.7, the influence of the pixels in the same location in the previous and next slice is assigned a weight 1.5, while a weight 1.3 is assigned to the influence of the north, south, east, west and diagonal pixels in the previous and next slices.

\[\begin{tabular}{ccc} \begin{tabular}{|c|c|c|} 1.3 & 1.3 & 1.3 \\ 1.3 & 1.5 & 1.3 \\ 1.3 & 1.3 & 1.3 \\ \end{tabular} & \begin{tabular}{|c|c|c|} 1.7 & 1.7 & 1.7 \\ 1.7 & 0 & 1.7 \\ 1.7 & 1.7 & 1.7 \\ \end{tabular} & \begin{tabular}{|c|c|c|} 1.3 & 1.3 & 1.3 \\ 1.5 & 1.5 & 1.3 \\ 1.3 & 1.3 & 1.3 \\ \end{tabular} \\ \end{tabular}\]

The user needs to set the neighborhood size using the SetNeighborhoodRadius functions. The details on the semantics of a neighborhood can be found in the documentation associated with the itkNeighborhood and related objects. NOTE: The size of the neighborhood must match with the size of the neighborhood weighting parameters set by the user.

For minimization of the MRF labeling function the MinimizeFunctional virtual method is called. For our current implementation we use the the iterated conditional modes (ICM) algorithm described by Besag in the paper ``On the Statistical Analysis of Dirty Pictures'' in J. Royal Stat. Soc. B, Vol. 48, 1986.

In each iteration, the algorithm visits each pixel in turn and determines whether to update its classification by computing the influence of the classification of the pixel's neighbors and of the intensity data. On each iteration after the first, we reexamine the classification of a pixel only if the classification of some of its neighbors has changed in the previous iteration. The pixels' classification is updated using a synchronous scheme (iteration by iteration) until the error reaches less than the threshold or the number of iteration exceed the maximum set number of iterations. Note: The current implementation supports betaMatrix default weight for two and three dimensional images only. The default for higher dimension is set to unity. This should be over ridded by custom weights after filter initialization.

See also:
Neighborhood
ImageIterator
NeighborhoodIterator
Classifier

Definition at line 129 of file itkMRFImageFilter.h.


Member Typedef Documentation

template<class TInputImage , class TClassifiedImage >
typedef ImageClassifierBase<TInputImage,TClassifiedImage> itk::MRFImageFilter< TInputImage, TClassifiedImage >::ClassifierType

Type definitions for classifier to be used for the MRF lavbelling.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

Definition at line 199 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef SmartPointer<const Self> itk::MRFImageFilter< TInputImage, TClassifiedImage >::ConstPointer
typedef DataObject::Pointer itk::ImageSource< TClassifiedImage >::DataObjectPointer [inherited]

Smart Pointer type to a DataObject.

Reimplemented from itk::ProcessObject.

Definition at line 62 of file itkImageSource.h.

STL Array of SmartPointers to DataObjects

Definition at line 103 of file itkProcessObject.h.

typedef DataObjectPointerArray::size_type itk::ProcessObject::DataObjectPointerArraySizeType [inherited]

Size type of an std::vector

Definition at line 112 of file itkProcessObject.h.

template<class TInputImage , class TClassifiedImage >
typedef LabelledImageIndexType::IndexValueType itk::MRFImageFilter< TInputImage, TClassifiedImage >::IndexValueType
template<class TInputImage , class TClassifiedImage >
typedef TInputImage::ConstPointer itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageConstPointer
template<class TInputImage , class TClassifiedImage >
typedef InputImageFaceListType::iterator itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageFaceListIterator

Definition at line 221 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef InputImageFacesCalculator::FaceListType itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageFaceListType

Definition at line 218 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef NeighborhoodAlgorithm::ImageBoundaryFacesCalculator< TInputImage > itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageFacesCalculator

Definition at line 215 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef ConstNeighborhoodIterator< TInputImage > itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageNeighborhoodIterator

Input image neighborhood iterator and kernel size typedef

Definition at line 209 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef InputImageNeighborhoodIterator::RadiusType itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageNeighborhoodRadiusType

Definition at line 212 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TInputImage::PixelType itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImagePixelType

Type definition for the input image pixel type.

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

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

Definition at line 152 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TInputImage::Pointer itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImagePointer
template<class TInputImage , class TClassifiedImage >
typedef ImageRegionConstIterator<TInputImage> itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageRegionConstIterator
template<class TInputImage , class TClassifiedImage >
typedef ImageRegionIterator<TInputImage> itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageRegionIterator

Type definition for the input image region iterator

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

Definition at line 158 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TInputImage::RegionType itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageRegionType

Type definition for the input image region type.

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

Definition at line 155 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TInputImage itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageType

Type definition for the input image.

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

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

Definition at line 144 of file itkMRFImageFilter.h.

typedef ImageToImageFilterDetail::ImageRegionCopier<itkGetStaticConstMacro(OutputImageDimension), itkGetStaticConstMacro(InputImageDimension)> itk::ImageToImageFilter< TInputImage, TClassifiedImage >::InputToOutputRegionCopierType [protected, inherited]

Typedef for the region copier function object that converts an input region to an output region.

Definition at line 164 of file itkImageToImageFilter.h.

typedef int itk::LightObject::InternalReferenceCountType [protected, inherited]

Define the type of the reference count according to the target. This allows the use of atomic operations

Definition at line 139 of file itkLightObject.h.

template<class TInputImage , class TClassifiedImage >
typedef LabelledImageFaceListType::iterator itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageFaceListIterator

Definition at line 237 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef LabelledImageFacesCalculator::FaceListType itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageFaceListType

Definition at line 234 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef NeighborhoodAlgorithm::ImageBoundaryFacesCalculator< TClassifiedImage > itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageFacesCalculator

Definition at line 231 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TClassifiedImage::IndexType itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageIndexType

Type definition for the classified image index type.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

Definition at line 184 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef NeighborhoodIterator< TClassifiedImage > itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageNeighborhoodIterator

Labelled image neighborhood interator typedef

Definition at line 225 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef LabelledImageNeighborhoodIterator::RadiusType itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageNeighborhoodRadiusType

Definition at line 228 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TClassifiedImage::OffsetType itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageOffsetType

Type definition for the classified image offset type.

Definition at line 188 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TClassifiedImage::PixelType itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImagePixelType

Type definitions for the classified image pixel type. It has to be the same type as the training image.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

Definition at line 177 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TClassifiedImage::Pointer itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImagePointer

Type definitions for the labelled image. It is derived from the training image.

Definition at line 173 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef ImageRegionIterator<TClassifiedImage> itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageRegionIterator

Type definition for the input image region iterator

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

Definition at line 192 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TClassifiedImage::RegionType itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelledImageRegionType

Type definitions for the classified image pixel type. It has to be the same type as the training image.

Definition at line 181 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef ImageRegionIterator< LabelStatusImageType > itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelStatusImageIterator [protected]

Definition at line 348 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef NeighborhoodIterator< LabelStatusImageType > itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelStatusImageNeighborhoodIterator [protected]

Labelled status image neighborhood interator typedef

Definition at line 352 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef LabelStatusImageType::Pointer itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelStatusImagePointer [protected]

Definition at line 347 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef Image<int,itkGetStaticConstMacro(InputImageDimension) > itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelStatusImageType [protected]

Definition at line 344 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef LabelStatusImageType::IndexType itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelStatusIndexType [protected]

Definition at line 345 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef LabelStatusImageType::RegionType itk::MRFImageFilter< TInputImage, TClassifiedImage >::LabelStatusRegionType [protected]

Definition at line 346 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TInputImage::SizeType itk::MRFImageFilter< TInputImage, TClassifiedImage >::NeighborhoodRadiusType

Radius typedef support.

Definition at line 205 of file itkMRFImageFilter.h.

typedef Superclass::OutputImagePixelType itk::ImageToImageFilter< TInputImage, TClassifiedImage >::OutputImagePixelType [inherited]

Reimplemented from itk::ImageSource< TClassifiedImage >.

Definition at line 79 of file itkImageToImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef Superclass::OutputImagePointer itk::MRFImageFilter< TInputImage, TClassifiedImage >::OutputImagePointer

Reimplemented from itk::ImageSource< TClassifiedImage >.

Definition at line 138 of file itkMRFImageFilter.h.

typedef Superclass::OutputImageRegionType itk::ImageToImageFilter< TInputImage, TClassifiedImage >::OutputImageRegionType [inherited]

Superclass typedefs.

Reimplemented from itk::ImageSource< TClassifiedImage >.

Definition at line 75 of file itkImageToImageFilter.h.

typedef TClassifiedImage itk::ImageSource< TClassifiedImage >::OutputImageType [inherited]

Some convenient typedefs.

Definition at line 65 of file itkImageSource.h.

typedef ImageToImageFilterDetail::ImageRegionCopier<itkGetStaticConstMacro(InputImageDimension), itkGetStaticConstMacro(OutputImageDimension)> itk::ImageToImageFilter< TInputImage, TClassifiedImage >::OutputToInputRegionCopierType [protected, inherited]

Typedef for the region copier function object that converts an output region to an input region.

Definition at line 169 of file itkImageToImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef SmartPointer<Self> itk::MRFImageFilter< TInputImage, TClassifiedImage >::Pointer
template<class TInputImage , class TClassifiedImage >
typedef MRFImageFilter itk::MRFImageFilter< TInputImage, TClassifiedImage >::Self

Standard class typedefs.

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

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

Definition at line 134 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TInputImage::SizeType itk::MRFImageFilter< TInputImage, TClassifiedImage >::SizeType

Size and value typedef support.

Definition at line 202 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef ImageToImageFilter<TInputImage,TClassifiedImage> itk::MRFImageFilter< TInputImage, TClassifiedImage >::Superclass
template<class TInputImage , class TClassifiedImage >
typedef TClassifiedImage::PixelType itk::MRFImageFilter< TInputImage, TClassifiedImage >::TrainingImagePixelType

Type definitions for the training image pixel type.

Definition at line 169 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
typedef TClassifiedImage::Pointer itk::MRFImageFilter< TInputImage, TClassifiedImage >::TrainingImagePointer

Type definitions for the training image.

Definition at line 166 of file itkMRFImageFilter.h.


Member Enumeration Documentation

template<class TInputImage , class TClassifiedImage >
enum itk::MRFImageFilter::StopConditionType
Enumerator:
MaximumNumberOfIterations 
ErrorTolerance 

Definition at line 299 of file itkMRFImageFilter.h.


Constructor & Destructor Documentation

template<class TInputImage , class TClassifiedImage >
itk::MRFImageFilter< TInputImage, TClassifiedImage >::MRFImageFilter (  )  [protected]
template<class TInputImage , class TClassifiedImage >
itk::MRFImageFilter< TInputImage, TClassifiedImage >::~MRFImageFilter (  )  [protected]

Member Function Documentation

virtual void itk::ProcessObject::AbortGenerateDataOff (  )  [virtual, inherited]
virtual void itk::ProcessObject::AbortGenerateDataOn (  )  [virtual, inherited]

Turn on and off the AbortGenerateData flag.

virtual void itk::ProcessObject::AddInput ( DataObject input  )  [protected, virtual, inherited]

Protected methods for setting inputs. Subclasses make use of them for setting input.

unsigned long itk::Object::AddObserver ( const EventObject event,
Command  
) [inherited]

Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects

unsigned long itk::Object::AddObserver ( const EventObject event,
Command  
) const [inherited]

Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects

virtual void itk::ProcessObject::AddOutput ( DataObject output  )  [protected, virtual, inherited]

Protected methods for setting outputs. Subclasses make use of them for getting output.

virtual void itk::ImageSource< TClassifiedImage >::AfterThreadedGenerateData ( void   )  [inline, protected, virtual, inherited]

If an imaging filter needs to perform processing after all processing threads have completed, the filter can can provide an implementation for AfterThreadedGenerateData(). The execution flow in the default GenerateData() method will be: 1) Allocate the output buffer 2) Call BeforeThreadedGenerateData() 3) Spawn threads, calling ThreadedGenerateData() in each thread. 4) Call AfterThreadedGenerateData() Note that this flow of control is only available if a filter provides a ThreadedGenerateData() method and NOT a GenerateData() method.

Definition at line 265 of file itkImageSource.h.

template<class TInputImage , class TClassifiedImage >
void itk::MRFImageFilter< TInputImage, TClassifiedImage >::Allocate (  )  [protected]

Allocate memory for labelled images.

virtual void itk::ImageSource< TClassifiedImage >::AllocateOutputs (  )  [protected, virtual, inherited]

The GenerateData method normally allocates the buffers for all of the outputs of a filter. Some filters may want to override this default behavior. For example, a filter may have multiple outputs with varying resolution. Or a filter may want to process data in place by grafting its input to its output.

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::ApplyMRFImageFilter (  )  [protected, virtual]

Apply MRF Classifier. In this example the images are labelled using Iterated Conditional Mode algorithm by J. Besag, "On statistical analysis of dirty pictures," J. Royal Stat. Soc. B, vol. 48, pp. 259-302, 1986.

virtual void itk::ImageSource< TClassifiedImage >::BeforeThreadedGenerateData ( void   )  [inline, protected, virtual, inherited]

If an imaging filter needs to perform processing after the buffer has been allocated but before threads are spawned, the filter can can provide an implementation for BeforeThreadedGenerateData(). The execution flow in the default GenerateData() method will be: 1) Allocate the output buffer 2) Call BeforeThreadedGenerateData() 3) Spawn threads, calling ThreadedGenerateData() in each thread. 4) Call AfterThreadedGenerateData() Note that this flow of control is only available if a filter provides a ThreadedGenerateData() method and NOT a GenerateData() method.

Definition at line 253 of file itkImageSource.h.

static void itk::LightObject::BreakOnError (  )  [static, inherited]

This method is called when itkExceptionMacro executes. It allows the debugger to break on error.

virtual void itk::ProcessObject::CacheInputReleaseDataFlags (  )  [protected, virtual, inherited]

Cache the state of any ReleaseDataFlag's on the inputs. While the filter is executing, we need to set the ReleaseDataFlag's on the inputs to false in case the current filter is implemented using a mini-pipeline (which will try to release the inputs). After the filter finishes, we restore the state of the ReleaseDataFlag's before the call to ReleaseInputs().

virtual void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::CallCopyInputRegionToOutputRegion ( OutputImageRegionType destRegion,
const InputImageRegionType srcRegion 
) [protected, virtual, inherited]

This function calls the actual region copier to do the mapping from input image space to output image space. It uses a Function object used for dispatching to various routines to copy an input region (start index and size) to an output region. For most filters, this is a trivial copy because most filters require the input dimension to match the output dimension. However, some filters like itk::UnaryFunctorImageFilter can support output images of a higher dimension that the input.

This function object is used by the default implementation of GenerateOutputInformation(). It can also be used in routines like ThreadedGenerateData() where a filter may need to map an input region to an output region.

The default copier uses a "dispatch pattern" to call one of three overloaded functions depending on whether the input and output images are the same dimension, the input is a higher dimension that the output, or the input is of a lower dimension than the output. The use of an overloaded function is required for proper compilation of the various cases.

For the latter two cases, trivial implementations are used. If the input image is a higher dimension than the output, the first portion of the input region is copied to the output region. If the input region is a lower dimension than the output, the input region information is copied into the first portion of the output region and the rest of the output region is set to zero.

If a filter needs a different default behavior, it can override this method.

virtual void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::CallCopyOutputRegionToInputRegion ( InputImageRegionType destRegion,
const OutputImageRegionType srcRegion 
) [protected, virtual, inherited]

This function calls the actual region copier to do the mapping from output image space to input image space. It uses a Function object used for dispatching to various routines to copy an output region (start index and size) to an input region. For most filters, this is a trivial copy because most filters require the input dimension to match the output dimension. However, some filters like itk::ExtractImageFilter can support output images of a lower dimension that the input.

This function object can be used by GenerateOutputInformation() to copy the input LargestPossibleRegion to the output LargestPossibleRegion and can also be used in GenerateData or ThreadedGenerateData() where a filter may need to map an output region to an input region.

The default copier uses a "dispatch pattern" to call one of three overloaded functions depending on whether the input and output images are the same dimension, the input is a higher dimension that the output, or the input is of a lower dimension than the output. The use of an overloaded function is required for proper compilation of the various cases.

For the latter two cases, trivial implementations are used. If the input image is a higher dimension than the output, the output region information is copied into the first portion of the input region and the rest of the input region is set to zero. If the input region is a lower dimension than the output, the first portion of the output region is copied to the input region.

If a filter needs a different default behavior, it can override this method. The ExtractImageFilter overrides this function object so that if the input image is a higher dimension than the output image, the filter can control "where" in the input image the output subimage is extracted (as opposed to mapping to first few dimensions of the input).

virtual LightObject::Pointer itk::Object::CreateAnother (  )  const [virtual, inherited]
virtual void itk::Object::DebugOff (  )  const [virtual, inherited]

Turn debugging output off.

virtual void itk::Object::DebugOn (  )  const [virtual, inherited]

Turn debugging output on.

virtual void itk::LightObject::Delete (  )  [virtual, inherited]

Delete an itk object. This method should always be used to delete an object when the new operator was used to create it. Using the C delete method will not work with reference counting.

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::DoNeighborhoodOperation ( const InputImageNeighborhoodIterator imageIter,
LabelledImageNeighborhoodIterator labelledIter,
LabelStatusImageNeighborhoodIterator labelStatusIter 
) [protected, virtual]
template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::EnlargeOutputRequestedRegion ( DataObject  )  [protected, virtual]

Give the process object a chance to indictate that it will produce more output than it was requested to produce. For example, many imaging filters must compute the entire output at once or can only produce output in complete slices. Such filters cannot handle smaller requested regions. These filters must provide an implementation of this method, setting the output requested region to the size they will produce. By default, a process object does not modify the size of the output requested region.

Reimplemented from itk::ProcessObject.

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::GenerateData ( void   )  [protected, virtual]

A version of GenerateData() specific for image processing filters. This implementation will split the processing across multiple threads. The buffer is allocated by this method. Then the BeforeThreadedGenerateData() method is called (if provided). Then, a series of threads are spawned each calling ThreadedGenerateData(). After all the threads have completed processing, the AfterThreadedGenerateData() method is called (if provided). If an image processing filter cannot be threaded, the filter should provide an implementation of GenerateData(). That implementation is responsible for allocating the output buffer. If a filter an be threaded, it should NOT provide a GenerateData() method but should provide a ThreadedGenerateData() instead.

See also:
ThreadedGenerateData()

Reimplemented from itk::ImageSource< TClassifiedImage >.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::GenerateInputRequestedRegion ( void   )  [protected, virtual]

What is the input requested region that is required to produce the output requested region? The base assumption for image processing filters is that the input requested region can be set to match the output requested region. If a filter requires more input (for instance a filter that uses neighborhoods needs more input than output to avoid introducing artificial boundary conditions) or less input (for instance a magnify filter) will have to override this method. In doing so, it should call its superclass' implementation as its first step. Note that imaging filters operate differently than the classes to this point in the class hierachy. Up till now, the base assumption has been that the largest possible region will be requested of the input.

This implementation of GenerateInputRequestedRegion() only processes the inputs that are a subclass of the ImageBase<InputImageDimension>. If an input is another type of DataObject (including an Image of a different dimension), they are skipped by this method. The subclasses of ImageToImageFilter are responsible for providing an implementation of GenerateInputRequestedRegion() when there are multiple inputs of different types.

See also:
ProcessObject::GenerateInputRequestedRegion(), ImageSource::GenerateInputRequestedRegion()

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

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::GenerateOutputInformation (  )  [protected, virtual]

Generate the information decribing the output data. The default implementation of this method will copy information from the input to the output. A filter may override this method if its output will have different information than its input. For instance, a filter that shrinks an image will need to provide an implementation for this method that changes the spacing of the pixels. Such filters should call their superclass' implementation of this method prior to changing the information values they need (i.e. GenerateOutputInformation() should call Superclass::GenerateOutputInformation() prior to changing the information.

Reimplemented from itk::ProcessObject.

virtual void itk::ProcessObject::GenerateOutputRequestedRegion ( DataObject output  )  [protected, virtual, inherited]

Given one output whose requested region has been set, how should the requested regions for the remaining outputs of the process object be set? By default, all the outputs are set to the same requested region. If a filter needs to produce different requested regions for each output, for instance an image processing filter producing several outputs at different resolutions, then that filter may override this method and set the requested regions appropriatedly.

Note that a filter producing multiple outputs of different types is required to override this method. The default implementation can only correctly handle multiple outputs of the same type.

Reimplemented in itk::MultiResolutionPyramidImageFilter< TInputImage, TOutputImage >, itk::RecursiveMultiResolutionPyramidImageFilter< TInputImage, TOutputImage >, itk::watershed::BoundaryResolver< TPixelType, TDimension >, itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >, itk::watershed::Relabeler< TScalarType, TImageDimension >, itk::watershed::Segmenter< TInputImage >, itk::watershed::SegmentTreeGenerator< TScalarType >, itk::watershed::Relabeler< ScalarType, itkGetStaticConstMacro(ImageDimension)>, itk::watershed::Segmenter< InputImageType >, and itk::watershed::SegmentTreeGenerator< ScalarType >.

virtual const bool& itk::ProcessObject::GetAbortGenerateData (  )  [virtual, inherited]

Get the AbortGenerateData flag for the process object. Process objects may handle premature termination of execution in different ways.

Command* itk::Object::GetCommand ( unsigned long  tag  )  [inherited]

Get the command associated with the given tag. NOTE: This returns a pointer to a Command, but it is safe to asign this to a Command::Pointer. Since Command inherits from LightObject, at this point in the code, only a pointer or a reference to the Command can be used.

bool itk::Object::GetDebug (  )  const [inherited]

Get the value of the debug flag.

template<class TInputImage , class TClassifiedImage >
virtual double itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetErrorTolerance (  )  const [virtual]

Set/Get the error tollerance level which is used as a threshold to quit the iterations

static bool itk::Object::GetGlobalWarningDisplay (  )  [static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

const InputImageType* itk::ImageToImageFilter< TInputImage, TClassifiedImage >::GetInput ( unsigned int  idx  )  [inherited]

Set/Get the image input of this process object.

Reimplemented from itk::ProcessObject.

const DataObject* itk::ProcessObject::GetInput ( unsigned int  idx  )  const [protected, inherited]

Method used internally for getting an input.

Reimplemented in itk::MeshToMeshFilter< TInputMesh, TOutputMesh >, and itk::MeshToMeshFilter< TInput, TOutput >.

const InputImageType* itk::ImageToImageFilter< TInputImage, TClassifiedImage >::GetInput ( void   )  [inherited]

Set/Get the image input of this process object.

DataObjectPointerArray& itk::ProcessObject::GetInputs (  )  [inline, inherited]

Return an array with all the inputs of this process object. This is useful for tracing back in the pipeline to construct graphs etc.

Definition at line 108 of file itkProcessObject.h.

template<class TInputImage , class TClassifiedImage >
virtual unsigned int itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetMaximumNumberOfIterations (  )  const [virtual]

Set/Get the number of iteration of the Iterated Conditional Mode (ICM) algorithm. A default value is set at 50 iterations.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

MetaDataDictionary& itk::Object::GetMetaDataDictionary ( void   )  [inherited]
Returns:
A reference to this objects MetaDataDictionary.
Warning:
This reference may be changed.
const MetaDataDictionary& itk::Object::GetMetaDataDictionary ( void   )  const [inherited]
Returns:
A constant reference to this objects MetaDataDictionary.
template<class TInputImage , class TClassifiedImage >
virtual std::vector<double> itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetMRFNeighborhoodWeight (  )  [inline, virtual]

Set the weighting parameters (used in MRF algorithms). This is a function allowing the users to set the weight matrix by providing a a 1D array of weights. The default implementation supports a 3 x 3 x 3 kernel. The labeler needs to be extended for a different kernel size.

Definition at line 292 of file itkMRFImageFilter.h.

virtual unsigned long itk::Object::GetMTime (  )  const [virtual, inherited]

Return this objects modified time.

Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::ImageToSpatialObjectRegistrationMethod< TFixedImage, TMovingSpatialObject >, itk::MultiResolutionImageRegistrationMethod< TFixedImage, TMovingImage >, itk::PointSetToImageRegistrationMethod< TFixedPointSet, TMovingImage >, itk::PointSetToPointSetRegistrationMethod< TFixedPointSet, TMovingPointSet >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::ImageAdaptor< TImage, TAccessor >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::TransformToDeformationFieldSource< TOutputImage, TTransformPrecisionType >, itk::ImageSpatialObject< TDimension, TPixelType >, itk::MeshSpatialObject< TMesh >, itk::SceneSpatialObject< TSpaceDimension >, itk::SpatialObject< TDimension >, itk::ImageAdaptor< TImage, Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< VectorImage< TPixelType, Dimension >, Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AddPixelAccessor< TImage::PixelType > >, itk::ImageSpatialObject< TDimension, unsigned char >, itk::SpatialObject< 3 >, and itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >.

Referenced by itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >::GetObjectMTime().

MultiThreader* itk::ProcessObject::GetMultiThreader (  )  [inline, inherited]

Return the multithreader used by this class.

Definition at line 284 of file itkProcessObject.h.

template<class TInputImage , class TClassifiedImage >
virtual const char* itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetNameOfClass (  )  const [virtual]

Run-time type information (and related methods).

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

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

template<class TInputImage , class TClassifiedImage >
const NeighborhoodRadiusType itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetNeighborhoodRadius (  )  const [inline]

Get the neighborhood radius

Definition at line 275 of file itkMRFImageFilter.h.

References HardConnectedComponentImageFilter::InputImageDimension.

template<class TInputImage , class TClassifiedImage >
virtual unsigned int itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetNumberOfClasses (  )  const [virtual]

Set/Get the number of classes.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

DataObjectPointerArraySizeType itk::ProcessObject::GetNumberOfInputs (  )  const [inline, inherited]

Get the size of the input vector. This is merely the size of the input vector, not the number of inputs that have valid DataObject's assigned. Use GetNumberOfValidRequiredInputs() to determine how many inputs are non-null.

Definition at line 118 of file itkProcessObject.h.

template<class TInputImage , class TClassifiedImage >
virtual const unsigned int& itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetNumberOfIterations (  )  [virtual]
DataObjectPointerArraySizeType itk::ProcessObject::GetNumberOfOutputs (  )  const [inline, inherited]

Return an array with all the outputs of this process object. This is useful for tracing forward in the pipeline to contruct graphs etc.

Definition at line 135 of file itkProcessObject.h.

virtual const unsigned int& itk::ProcessObject::GetNumberOfRequiredInputs (  )  [protected, virtual, inherited]

Protected methods for setting inputs. Subclasses make use of them for setting input.

virtual const unsigned int& itk::ProcessObject::GetNumberOfRequiredOutputs (  )  [protected, virtual, inherited]

Protected methods for setting outputs. Subclasses make use of them for getting output.

virtual const int& itk::ProcessObject::GetNumberOfThreads (  )  [virtual, inherited]

Get/Set the number of threads to create when executing.

Referenced by itk::BSplineScatteredDataPointSetToImageFilter< TInputPointSet, TOutputImage >::SplitRequestedRegion().

virtual DataObjectPointerArraySizeType itk::ProcessObject::GetNumberOfValidRequiredInputs (  )  const [virtual, inherited]

Get the number of valid inputs. This is the number of non-null entries in the input vector in the first NumberOfRequiredInputs slots. This method is used to determine whether the necessary required inputs have been set. Subclasses of ProcessObject may override this implementation if the required inputs are not the first slots in input vector.

Reimplemented in itk::MultiResolutionPDEDeformableRegistration< TFixedImage, TMovingImage, TDeformationField, TRealType >, and itk::PDEDeformableRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >.

OutputImageType* itk::ImageSource< TClassifiedImage >::GetOutput ( void   )  [inherited]

Get the output data of this process object. The output of this function is not valid until an appropriate Update() method has been called, either explicitly or implicitly. Both the filter itself and the data object have Update() methods, and both methods update the data. Here are three ways to use GetOutput() and make sure the data is valid. In these examples, image is a pointer to some Image object, and the particular ProcessObjects involved are filters. The same examples apply to non-image (e.g. Mesh) data as well.

   anotherFilter->SetInput( someFilter->GetOutput() );
   anotherFilter->Update();

In this situation, someFilter and anotherFilter are said to constitute a pipeline.

   image = someFilter->GetOutput();
   image->Update();
   someFilter->Update();
   image = someFilter->GetOutput();

(In the above example, the two lines of code can be in either order.)

Note that Update() is not called automatically except within a pipeline as in the first example. When streaming (using a StreamingImageFilter) is activated, it may be more efficient to use a pipeline than to call Update() once for each filter in turn.

For an image, the data generated is for the requested Region, which can be set using ImageBase::SetRequestedRegion(). By default, the largest possible region is requested.

For Filters which have multiple outputs of different types, the GetOutput() method assumes the output is of OutputImageType. For the GetOutput(unsigned int) method, a dynamic_cast is performed incase the filter has outputs of different types or image types. Derived classes should have names get methods for these outputs.

OutputImageType* itk::ImageSource< TClassifiedImage >::GetOutput ( unsigned int  idx  )  [inherited]

Get the output data of this process object. The output of this function is not valid until an appropriate Update() method has been called, either explicitly or implicitly. Both the filter itself and the data object have Update() methods, and both methods update the data. Here are three ways to use GetOutput() and make sure the data is valid. In these examples, image is a pointer to some Image object, and the particular ProcessObjects involved are filters. The same examples apply to non-image (e.g. Mesh) data as well.

   anotherFilter->SetInput( someFilter->GetOutput() );
   anotherFilter->Update();

In this situation, someFilter and anotherFilter are said to constitute a pipeline.

   image = someFilter->GetOutput();
   image->Update();
   someFilter->Update();
   image = someFilter->GetOutput();

(In the above example, the two lines of code can be in either order.)

Note that Update() is not called automatically except within a pipeline as in the first example. When streaming (using a StreamingImageFilter) is activated, it may be more efficient to use a pipeline than to call Update() once for each filter in turn.

For an image, the data generated is for the requested Region, which can be set using ImageBase::SetRequestedRegion(). By default, the largest possible region is requested.

For Filters which have multiple outputs of different types, the GetOutput() method assumes the output is of OutputImageType. For the GetOutput(unsigned int) method, a dynamic_cast is performed incase the filter has outputs of different types or image types. Derived classes should have names get methods for these outputs.

Reimplemented from itk::ProcessObject.

const DataObject* itk::ProcessObject::GetOutput ( unsigned int  idx  )  const [protected, inherited]

Method used internally for getting an output.

DataObjectPointerArray& itk::ProcessObject::GetOutputs (  )  [inline, inherited]

Return an array with all the outputs of this process object. This is useful for tracing forward in the pipeline to contruct graphs etc.

Definition at line 133 of file itkProcessObject.h.

virtual const float& itk::ProcessObject::GetProgress (  )  [virtual, inherited]

Get the execution progress of a process object. The progress is a floating number in [0,1] with 0 meaning no progress and 1 meaning the filter has completed execution.

Referenced by itk::XMLFilterWatcher::ShowProgress().

virtual int itk::LightObject::GetReferenceCount (  )  const [inline, virtual, inherited]

Gets the reference count on this object.

Definition at line 106 of file itkLightObject.h.

virtual const bool& itk::ProcessObject::GetReleaseDataBeforeUpdateFlag (  )  [virtual, inherited]

Turn on/off the flags to control whether the bulk data belonging to the outputs of this ProcessObject are released/reallocated during an Update(). In limited memory scenarios, a user may want to force the elements of a pipeline to release any bulk data that is going to be regenerated anyway during an Update() in order to control peak memory allocation. Note that this flag is different from the ReleaseDataFlag. ReleaseDataFlag manages the deallocation of a ProcessObject's bulk output data once that data has been consumed by a downstream ProcessObject. The ReleaseDataBeforeUpdateFlag manages the deallocation/reallocation of bulk data during a pipeline update to control peak memory utilization. Default value is on.

virtual bool itk::ProcessObject::GetReleaseDataFlag (  )  const [virtual, inherited]

Turn on/off the flags to control whether the bulk data belonging to the outputs of this ProcessObject are released after being used by a downstream ProcessObject. Default value is off. Another options for controlling memory utilization is the ReleaseDataBeforeUpdateFlag.

template<class TInputImage , class TClassifiedImage >
virtual double itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetSmoothingFactor (  )  const [virtual]

Set/Get the degree of smoothing desired

template<class TInputImage , class TClassifiedImage >
virtual const StopConditionType& itk::MRFImageFilter< TInputImage, TClassifiedImage >::GetStopCondition (  )  [virtual]

Get condition that stops the MRF filter (Number of Iterations / Error tolerance )

static void itk::Object::GlobalWarningDisplayOff (  )  [inline, static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Definition at line 100 of file itkObject.h.

References itk::Object::SetGlobalWarningDisplay().

static void itk::Object::GlobalWarningDisplayOn (  )  [inline, static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Definition at line 98 of file itkObject.h.

References itk::Object::SetGlobalWarningDisplay().

virtual void itk::ImageSource< TClassifiedImage >::GraftNthOutput ( unsigned int  idx,
DataObject output 
) [virtual, inherited]

Graft the specified data object onto this ProcessObject's idx'th output. This is similar to the GraftOutput method except it allows you to specify which output is affected. The specified index must be a valid output number (less than ProcessObject::GetNumberOfOutputs()). See the GraftOutput for general usage information.

virtual void itk::ImageSource< TClassifiedImage >::GraftOutput ( DataObject output  )  [virtual, inherited]

Graft the specified DataObject onto this ProcessObject's output. This method grabs a handle to the specified DataObject's bulk data to used as its output's own bulk data. It also copies the region ivars (RequestedRegion, BufferedRegion, LargestPossibleRegion) and meta-data (Spacing, Origin) from the specified data object into this filter's output data object. Most importantly, however, it leaves the Source ivar untouched so the original pipeline routing is intact. This method is used when a process object is implemented using a mini-pipeline which is defined in its GenerateData() method. The usage is:

    // setup the mini-pipeline to process the input to this filter
    firstFilterInMiniPipeline->SetInput( this->GetInput() );

    // setup the mini-pipeline to calculate the correct regions
    // and write to the appropriate bulk data block
    lastFilterInMiniPipeline->GraftOutput( this->GetOutput() );

    // execute the mini-pipeline
    lastFilterInMiniPipeline->Update();

    // graft the mini-pipeline output back onto this filter's output.
    // this is needed to get the appropriate regions passed back.
    this->GraftOutput( lastFilterInMiniPipeline->GetOutput() );

For proper pipeline execution, a filter using a mini-pipeline must implement the GenerateInputRequestedRegion(), GenerateOutputRequestedRegion(), GenerateOutputInformation() and EnlargeOutputRequestedRegion() methods as necessary to reflect how the mini-pipeline will execute (in other words, the outer filter's pipeline mechanism must be consistent with what the mini-pipeline will do).

bool itk::Object::HasObserver ( const EventObject event  )  const [inherited]

Return true if an observer is registered for this event.

void itk::Object::InvokeEvent ( const EventObject  )  const [inherited]

Call Execute on all the Commands observing this event id. The actions triggered by this call doesn't modify this object.

void itk::Object::InvokeEvent ( const EventObject  )  [inherited]

Call Execute on all the Commands observing this event id.

virtual DataObjectPointer itk::ImageSource< TClassifiedImage >::MakeOutput ( unsigned int  idx  )  [virtual, inherited]

Make a DataObject of the correct type to used as the specified output. Every ProcessObject subclass must be able to create a DataObject that can be used as a specified output. This method is automatically called when DataObject::DisconnectPipeline() is called. DataObject::DisconnectPipeline, disconnects a data object from being an output of its current source. When the data object is disconnected, the ProcessObject needs to construct a replacement output data object so that the ProcessObject is in a valid state. So DataObject::DisconnectPipeline eventually calls ProcessObject::MakeOutput. Note that MakeOutput always returns a SmartPointer to a DataObject. If a subclass of ImageSource has multiple outputs of different types, then that class must provide an implementation of MakeOutput().

Reimplemented from itk::ProcessObject.

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::MinimizeFunctional (  )  [protected, virtual]

Minimization algorithm to be used.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

virtual void itk::Object::Modified (  )  const [virtual, inherited]

Update the modification time for this object. Many filters rely on the modification time to determine if they need to recompute their data.

Reimplemented in itk::NormalizeImageFilter< TInputImage, TOutputImage >, itk::ImageAdaptor< TImage, TAccessor >, itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, TFilter >, itk::GrayscaleDilateImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleErodeImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >, itk::MorphologicalGradientImageFilter< TInputImage, TOutputImage, TKernel >, itk::ImageAdaptor< TImage, Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< VectorImage< TPixelType, Dimension >, Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AddPixelAccessor< TImage::PixelType > >, and itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, RankImageFilter< TInputImage, TInputImage, FlatStructuringElement< ::itk::GetImageDimension< TInputImage >::ImageDimension > > >.

Referenced by itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::InsertNarrowBandNode(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBand(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandInnerRadius(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandTotalRadius(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< TInputHistogram >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

template<class TInputImage , class TClassifiedImage >
static Pointer itk::MRFImageFilter< TInputImage, TClassifiedImage >::New (  )  [static]

Method for creation through the object factory.

Reimplemented from itk::Object.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

virtual void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::PopBackInput (  )  [virtual, inherited]

Push/Pop the input of this process object. These methods allow a filter to model its input vector as a queue or stack. These routines may not be appropriate for all filters, especially filters with different types of inputs. These routines follow the semantics of STL.

The routines are useful for applications that need to process "rolling" sets of images. For instance, if an application has 10 images and they need to run a filter on images 1, 2, 3, 4, then run the filter on images 2, 3, 4, 5, then run the filter on images 3, 4, 5, 6, the application can accomplish this by popping an input off the front of the input list and push a new image onto the back of input list. Again, this only makes sense for filters that single type of input.

Other uses are also possible. For a single input filter, pushing and popping inputs allow the application to temporarily replace an input to a filter.

Reimplemented from itk::ProcessObject.

virtual void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::PopFrontInput (  )  [virtual, inherited]

Push/Pop the input of this process object. These methods allow a filter to model its input vector as a queue or stack. These routines may not be appropriate for all filters, especially filters with different types of inputs. These routines follow the semantics of STL.

The routines are useful for applications that need to process "rolling" sets of images. For instance, if an application has 10 images and they need to run a filter on images 1, 2, 3, 4, then run the filter on images 2, 3, 4, 5, then run the filter on images 3, 4, 5, 6, the application can accomplish this by popping an input off the front of the input list and push a new image onto the back of input list. Again, this only makes sense for filters that single type of input.

Other uses are also possible. For a single input filter, pushing and popping inputs allow the application to temporarily replace an input to a filter.

Reimplemented from itk::ProcessObject.

virtual void itk::ProcessObject::PrepareOutputs (  )  [virtual, inherited]

An opportunity to deallocate a ProcessObject's bulk data storage. Some filters may wish to reuse existing bulk data storage to avoid unnecessary deallocation/allocation sequences. The default implementation calls Initialize() on each output. DataObject::Initialize() frees its bulk data by default.

Reimplemented in itk::WatershedImageFilter< TInputImage >.

void itk::LightObject::Print ( std::ostream &  os,
Indent  indent = 0 
) const [inherited]

Cause the object to print itself out.

Referenced by itk::WeakPointer< ProcessObject >::Print().

virtual void itk::LightObject::PrintHeader ( std::ostream &  os,
Indent  indent 
) const [protected, virtual, inherited]

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.

bool itk::Object::PrintObservers ( std::ostream &  os,
Indent  indent 
) const [protected, inherited]
template<class TInputImage , class TClassifiedImage >
void itk::MRFImageFilter< TInputImage, TClassifiedImage >::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, TClassifiedImage >.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

virtual void itk::LightObject::PrintTrailer ( std::ostream &  os,
Indent  indent 
) const [protected, virtual, inherited]

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.

virtual void itk::ProcessObject::PropagateRequestedRegion ( DataObject output  )  [virtual, inherited]

Send the requested region information back up the pipeline (to the filters that preceed this one).

Reimplemented in itk::StreamingImageFilter< TInputImage, TOutputImage >, and itk::VTKImageImport< TOutputImage >.

virtual void itk::ProcessObject::PropagateResetPipeline (  )  [protected, virtual, inherited]

Called to allocate the input array. Copies old inputs. Propagate a call to ResetPipeline() up the pipeline. Called only from DataObject.

virtual void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::PushBackInput ( const InputImageType image  )  [virtual, inherited]

Push/Pop the input of this process object. These methods allow a filter to model its input vector as a queue or stack. These routines may not be appropriate for all filters, especially filters with different types of inputs. These routines follow the semantics of STL.

The routines are useful for applications that need to process "rolling" sets of images. For instance, if an application has 10 images and they need to run a filter on images 1, 2, 3, 4, then run the filter on images 2, 3, 4, 5, then run the filter on images 3, 4, 5, 6, the application can accomplish this by popping an input off the front of the input list and push a new image onto the back of input list. Again, this only makes sense for filters that single type of input.

Other uses are also possible. For a single input filter, pushing and popping inputs allow the application to temporarily replace an input to a filter.

void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::PushBackInput ( const DataObject input  )  [inline, protected, virtual, inherited]

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::ProcessObject.

Definition at line 251 of file itkImageToImageFilter.h.

virtual void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::PushFrontInput ( const InputImageType image  )  [virtual, inherited]

Push/Pop the input of this process object. These methods allow a filter to model its input vector as a queue or stack. These routines may not be appropriate for all filters, especially filters with different types of inputs. These routines follow the semantics of STL.

The routines are useful for applications that need to process "rolling" sets of images. For instance, if an application has 10 images and they need to run a filter on images 1, 2, 3, 4, then run the filter on images 2, 3, 4, 5, then run the filter on images 3, 4, 5, 6, the application can accomplish this by popping an input off the front of the input list and push a new image onto the back of input list. Again, this only makes sense for filters that single type of input.

Other uses are also possible. For a single input filter, pushing and popping inputs allow the application to temporarily replace an input to a filter.

void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::PushFrontInput ( const DataObject input  )  [inline, protected, virtual, inherited]

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::ProcessObject.

Definition at line 253 of file itkImageToImageFilter.h.

virtual void itk::Object::Register (  )  const [virtual, inherited]

Increase the reference count (mark as used by another object).

Reimplemented from itk::LightObject.

virtual void itk::ProcessObject::ReleaseDataBeforeUpdateFlagOff (  )  [virtual, inherited]

Turn on/off the flags to control whether the bulk data belonging to the outputs of this ProcessObject are released/reallocated during an Update(). In limited memory scenarios, a user may want to force the elements of a pipeline to release any bulk data that is going to be regenerated anyway during an Update() in order to control peak memory allocation. Note that this flag is different from the ReleaseDataFlag. ReleaseDataFlag manages the deallocation of a ProcessObject's bulk output data once that data has been consumed by a downstream ProcessObject. The ReleaseDataBeforeUpdateFlag manages the deallocation/reallocation of bulk data during a pipeline update to control peak memory utilization. Default value is on.

virtual void itk::ProcessObject::ReleaseDataBeforeUpdateFlagOn (  )  [virtual, inherited]

Turn on/off the flags to control whether the bulk data belonging to the outputs of this ProcessObject are released/reallocated during an Update(). In limited memory scenarios, a user may want to force the elements of a pipeline to release any bulk data that is going to be regenerated anyway during an Update() in order to control peak memory allocation. Note that this flag is different from the ReleaseDataFlag. ReleaseDataFlag manages the deallocation of a ProcessObject's bulk output data once that data has been consumed by a downstream ProcessObject. The ReleaseDataBeforeUpdateFlag manages the deallocation/reallocation of bulk data during a pipeline update to control peak memory utilization. Default value is on.

void itk::ProcessObject::ReleaseDataFlagOff (  )  [inline, inherited]

Turn on/off the flags to control whether the bulk data belonging to the outputs of this ProcessObject are released after being used by a downstream ProcessObject. Default value is off. Another options for controlling memory utilization is the ReleaseDataBeforeUpdateFlag.

Definition at line 257 of file itkProcessObject.h.

void itk::ProcessObject::ReleaseDataFlagOn (  )  [inline, inherited]

Turn on/off the flags to control whether the bulk data belonging to the outputs of this ProcessObject are released after being used by a downstream ProcessObject. Default value is off. Another options for controlling memory utilization is the ReleaseDataBeforeUpdateFlag.

Definition at line 256 of file itkProcessObject.h.

virtual void itk::ProcessObject::ReleaseInputs (  )  [protected, virtual, inherited]

A filter may need to release its input's bulk data after it has finished calculating a new output. The filter may need to release the inputs because the user has turned on the ReleaseDataFlag or it may need to release the inputs because the filter is an "in place" filter and it has overwritten its input with its output data. The implementation here simply checks the ReleaseDataFlag of the inputs. InPlaceImageFilter overrides this method so release the input it has overwritten.

See also:
InPlaceImageFilter::ReleaseInputs()

Reimplemented in itk::InPlaceImageFilter< TInputImage, TOutputImage >, itk::InPlaceLabelMapFilter< TInputImage >, itk::InPlaceImageFilter< TInputImage, TOutputImage >, itk::InPlaceImageFilter< TDeformationField, TDeformationField >, itk::InPlaceImageFilter< TInputImage1, Functor::MakeJoin< TInputImage1, TInputImage2 >::ImageType >, itk::InPlaceImageFilter< TInputImage >, itk::InPlaceImageFilter< TInputImage, TSparseOutputImage >, itk::InPlaceImageFilter< TInputImage1, TOutputImage >, itk::InPlaceImageFilter< Image< TInputPixel1, NDimension >, Image< std::complex< TOutputPixel >, NDimension > >, itk::InPlaceImageFilter< TFeatureImage, TOutputImage >, itk::InPlaceImageFilter< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >, itk::InPlaceImageFilter< TLabelImage, TOutputImage >, itk::InPlaceImageFilter< FeatureImageType, ImageType >, itk::InPlaceImageFilter< TInputImageType, TSparseOutputImageType >, itk::InPlaceImageFilter< TImage, TImage >, and itk::InPlaceLabelMapFilter< TImage >.

void itk::Object::RemoveAllObservers (  )  [inherited]

Remove all observers .

virtual void itk::ProcessObject::RemoveInput ( DataObject input  )  [protected, virtual, inherited]

Protected methods for setting inputs. Subclasses make use of them for setting input.

void itk::Object::RemoveObserver ( unsigned long  tag  )  [inherited]

Remove the observer with this tag value.

virtual void itk::ProcessObject::RemoveOutput ( DataObject output  )  [protected, virtual, inherited]

Protected methods for setting outputs. Subclasses make use of them for getting output.

virtual void itk::ProcessObject::ResetPipeline (  )  [virtual, inherited]

Reset the pipeline. If an exception is thrown during an Update(), the pipeline may be in an inconsistent state. This method clears the internal state of the pipeline so Update() can be called.

virtual void itk::ProcessObject::RestoreInputReleaseDataFlags (  )  [protected, virtual, inherited]

Restore the cached input ReleaseDataFlags.

virtual void itk::ProcessObject::SetAbortGenerateData ( bool  _arg  )  [virtual, inherited]

Set the AbortGenerateData flag for the process object. Process objects may handle premature termination of execution in different ways.

template<class TInputImage , class TClassifiedImage >
void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetClassifier ( typename ClassifierType::Pointer  ptrToClassifier  ) 

Set the pointer to the classifer being used.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

void itk::Object::SetDebug ( bool  debugFlag  )  const [inherited]

Set the value of the debug flag. A non-zero value turns debugging on.

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetErrorTolerance ( double  _arg  )  [virtual]

Set/Get the error tollerance level which is used as a threshold to quit the iterations

static void itk::Object::SetGlobalWarningDisplay ( bool  flag  )  [static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().

virtual void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::SetInput ( unsigned  int,
const TInputImage *  image 
) [virtual, inherited]

Set/Get the image input of this process object.

virtual void itk::ImageToImageFilter< TInputImage, TClassifiedImage >::SetInput ( const InputImageType image  )  [virtual, inherited]

Set/Get the image input of this process object.

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetMaximumNumberOfIterations ( unsigned int  _arg  )  [virtual]

Set/Get the number of iteration of the Iterated Conditional Mode (ICM) algorithm. A default value is set at 50 iterations.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

void itk::Object::SetMetaDataDictionary ( const MetaDataDictionary rhs  )  [inherited]
Returns:
Set the MetaDataDictionary
template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetMRFNeighborhoodWeight ( std::vector< double >  BetaMatrix  )  [virtual]

Set the weighting parameters (used in MRF algorithms). This is a function allowing the users to set the weight matrix by providing a a 1D array of weights. The default implementation supports a 3 x 3 x 3 kernel. The labeler needs to be extended for a different kernel size.

template<class TInputImage , class TClassifiedImage >
void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetNeighborhoodRadius ( const unsigned  long  ) 

Sets the radius for the neighborhood, calculates size from the radius, and allocates storage.

template<class TInputImage , class TClassifiedImage >
void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetNeighborhoodRadius ( const unsigned long *  radiusArray  ) 
template<class TInputImage , class TClassifiedImage >
void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetNeighborhoodRadius ( const NeighborhoodRadiusType  ) 

Set the neighborhood radius

virtual void itk::ProcessObject::SetNthInput ( unsigned int  num,
DataObject input 
) [protected, virtual, inherited]
virtual void itk::ProcessObject::SetNthOutput ( unsigned int  num,
DataObject output 
) [protected, virtual, inherited]
template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetNumberOfClasses ( unsigned int  _arg  )  [virtual]

Set/Get the number of classes.

Reimplemented in itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >.

void itk::ProcessObject::SetNumberOfInputs ( unsigned int  num  )  [protected, inherited]

Called to allocate the input array. Copies old inputs.

void itk::ProcessObject::SetNumberOfOutputs ( unsigned int  num  )  [protected, inherited]

Called to allocate the output array. Copies old outputs.

virtual void itk::ProcessObject::SetNumberOfRequiredInputs ( unsigned int  _arg  )  [protected, virtual, inherited]

Protected methods for setting inputs. Subclasses make use of them for setting input.

virtual void itk::ProcessObject::SetNumberOfRequiredOutputs ( unsigned int  _arg  )  [protected, virtual, inherited]

Protected methods for setting outputs. Subclasses make use of them for getting output.

virtual void itk::ProcessObject::SetNumberOfThreads ( int  _arg  )  [virtual, inherited]
virtual void itk::ProcessObject::SetProgress ( float  _arg  )  [virtual, inherited]

Set the execution progress of a process object. The progress is a floating number in [0,1] with 0 meaning no progress and 1 meaning the filter has completed execution. The ProgressEvent is NOT invoked.

virtual void itk::Object::SetReferenceCount ( int   )  [virtual, inherited]

Sets the reference count (use with care)

Reimplemented from itk::LightObject.

virtual void itk::ProcessObject::SetReleaseDataBeforeUpdateFlag ( bool  _arg  )  [virtual, inherited]

Turn on/off the flags to control whether the bulk data belonging to the outputs of this ProcessObject are released/reallocated during an Update(). In limited memory scenarios, a user may want to force the elements of a pipeline to release any bulk data that is going to be regenerated anyway during an Update() in order to control peak memory allocation. Note that this flag is different from the ReleaseDataFlag. ReleaseDataFlag manages the deallocation of a ProcessObject's bulk output data once that data has been consumed by a downstream ProcessObject. The ReleaseDataBeforeUpdateFlag manages the deallocation/reallocation of bulk data during a pipeline update to control peak memory utilization. Default value is on.

virtual void itk::ProcessObject::SetReleaseDataFlag ( bool  flag  )  [virtual, inherited]

Turn on/off the flags to control whether the bulk data belonging to the outputs of this ProcessObject are released after being used by a downstream ProcessObject. Default value is off. Another options for controlling memory utilization is the ReleaseDataBeforeUpdateFlag.

template<class TInputImage , class TClassifiedImage >
virtual void itk::MRFImageFilter< TInputImage, TClassifiedImage >::SetSmoothingFactor ( double  _arg  )  [virtual]

Set/Get the degree of smoothing desired

virtual int itk::ImageSource< TClassifiedImage >::SplitRequestedRegion ( int  i,
int  num,
OutputImageRegionType splitRegion 
) [protected, virtual, inherited]

Split the output's RequestedRegion into "num" pieces, returning region "i" as "splitRegion". This method is called "num" times. The regions must not overlap. The method returns the number of pieces that the routine is capable of splitting the output RequestedRegion, i.e. return value is less than or equal to "num".

virtual void itk::ImageSource< TClassifiedImage >::ThreadedGenerateData ( const OutputImageRegionType outputRegionForThread,
int  threadId 
) [protected, virtual, inherited]

If an imaging filter can be implemented as a multithreaded algorithm, the filter will provide an implementation of ThreadedGenerateData(). This superclass will automatically split the output image into a number of pieces, spawn multiple threads, and call ThreadedGenerateData() in each thread. Prior to spawning threads, the BeforeThreadedGenerateData() method is called. After all the threads have completed, the AfterThreadedGenerateData() method is called. If an image processing filter cannot support threading, that filter should provide an implementation of the GenerateData() method instead of providing an implementation of ThreadedGenerateData(). If a filter provides a GenerateData() method as its implementation, then the filter is responsible for allocating the output data. If a filter provides a ThreadedGenerateData() method as its implementation, then the output memory will allocated automatically by this superclass. The ThreadedGenerateData() method should only produce the output specified by "outputThreadRegion" parameter. ThreadedGenerateData() cannot write to any other portion of the output image (as this is responsibility of a different thread).

See also:
GenerateData(), SplitRequestedRegion()
static ITK_THREAD_RETURN_TYPE itk::ImageSource< TClassifiedImage >::ThreaderCallback ( void *  arg  )  [static, protected, inherited]

Static function used as a "callback" by the MultiThreader. The threading library will call this routine for each thread, which will delegate the control to ThreadedGenerateData().

virtual void itk::Object::UnRegister (  )  const [virtual, inherited]

Decrease the reference count (release by another object).

Reimplemented from itk::LightObject.

virtual void itk::ProcessObject::Update (  )  [virtual, inherited]

Bring this filter up-to-date. Update() checks modified times against last execution times, and re-executes objects if necessary. A side effect of this method is that the whole pipeline may execute in order to bring this filter up-to-date. This method updates the currently prescribed requested region. If no requested region has been set on the output, then the requested region will be set to the largest possible region. Once the requested region is set, Update() will make sure the specified requested region is up-to-date. This is a confusing side effect to users who are just calling Update() on a filter. A first call to Update() will cause the largest possible region to be updated. A second call to Update() will update that same region. If a modification to the upstream pipeline cause a filter to have a different largest possible region, this second call to Update() will not cause the output requested region to be reset to the new largest possible region. Instead, the output requested region will be the same as the last time Update() was called. To have a filter always to produce its largest possible region, users should call UpdateLargestPossibleRegion() instead.

Reimplemented in itk::CoreAtomImageToUnaryCorrespondenceMatrixProcess< TSourceImage >, itk::MedialNodePairCorrespondenceProcess< TSourceImage >, itk::MedialNodeTripletCorrespondenceProcess< TSourceImage >, itk::CoreAtomImageToDistanceMatrixProcess< TSourceImage >, itk::ImageFileWriter< TInputImage >, and itk::ImageSeriesWriter< TInputImage, TOutputImage >.

virtual void itk::ProcessObject::UpdateLargestPossibleRegion (  )  [virtual, inherited]

Like Update(), but sets the output requested region to the largest possible region for the output. This is the method users should call if they want the entire dataset to be processed. If a user wants to update the same output region as a previous call to Update() or a previous call to UpdateLargestPossibleRegion(), then they should call the method Update().

virtual void itk::ProcessObject::UpdateOutputData ( DataObject output  )  [virtual, inherited]

Actually generate new output

Reimplemented in itk::StreamingImageFilter< TInputImage, TOutputImage >.

virtual void itk::ProcessObject::UpdateOutputInformation (  )  [virtual, inherited]

Update the information decribing the output data. This method transverses up the pipeline gathering modified time information. On the way back down the pipeline, this method calls GenerateOutputInformation() to set any necessary information about the output data objects. For instance, a filter that shrinks an image will need to provide an implementation for GenerateOutputInformation() that changes the spacing of the pixels. Such filters should call their superclass' implementation of GenerateOutputInformation prior to changing the information values they need (i.e. GenerateOutputInformation() should call Superclass::GenerateOutputInformation() prior to changing the information.

Reimplemented in itk::watershed::Segmenter< TInputImage >, itk::VTKImageImport< TOutputImage >, and itk::watershed::Segmenter< InputImageType >.

void itk::ProcessObject::UpdateProgress ( float  amount  )  [inherited]

Update the progress of the process object.

Sets the Progress ivar to amount and invokes any observers for the ProgressEvent. The parameter amount should be in [0,1] and is the cumulative (not incremental) progress.


Member Data Documentation

template<class TInputImage , class TClassifiedImage >
const unsigned int itk::MRFImageFilter< TInputImage, TClassifiedImage >::ClassifiedImageDimension = TClassifiedImage::ImageDimension [static]

Labelled Image dimension

Definition at line 196 of file itkMRFImageFilter.h.

template<class TInputImage , class TClassifiedImage >
const unsigned int itk::MRFImageFilter< TInputImage, TClassifiedImage >::InputImageDimension = TInputImage::ImageDimension [static]

Image dimension

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

Definition at line 163 of file itkMRFImageFilter.h.

Time when GenerateOutputInformation was last called.

Definition at line 431 of file itkProcessObject.h.

Number of uses of this object by other objects.

Definition at line 144 of file itkLightObject.h.

Mutex lock to protect modification to the reference count

Definition at line 147 of file itkLightObject.h.

bool itk::ProcessObject::m_Updating [protected, inherited]

These ivars are made protected so filters like itkStreamingImageFilter can access them directly. This flag indicates when the pipeline is executing. It prevents infinite recursion when pipelines have loops.

Definition at line 428 of file itkProcessObject.h.

const unsigned int itk::ImageToImageFilter< TInputImage, TClassifiedImage >::OutputImageDimension [static, inherited]

ImageDimension constants

Reimplemented from itk::ImageSource< TClassifiedImage >.

Definition at line 92 of file itkImageToImageFilter.h.


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

Generated at Tue Jul 13 2010 00:23:59 for ITK by doxygen 1.7.1 written by Dimitri van Heesch, © 1997-2000