itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage > Class Template Reference

#include <itkImplicitManifoldNormalVectorFilter.h>

Inheritance diagram for itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >:

[legend]Collaboration diagram for itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >:

[legend]List of all members.

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Detailed Description

template<class TInputImage, class TSparseOutputImage>
class itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >

This class implements the filter for computing the normal vectors from a scalar implicit function (i.e. a levelset image) and processing them.

This is a ready-to-use class for filtering normal vectors of an implicit manifold image. The normal vectors of the input image are computed and processed in a band where the values of the input image fall in the region [IsoLevelLow, IsoLevelHigh]. The processing is done by m_NormalFunction. This class also defines a Halt method which uses the iteration counter and the parameter m_MaxIteration to determine when to stop the processing.

INPUTS

The input is a scalar image. Even though this can be any scalar image, this filter class is intended to work with the image of an implicit function. One such example is the output of the SparseFieldLevelSetImageFilter class.

OUTPUTS

The output is a sparse image. The m_Data member variables of the nodes of the sparse image will contain the filtered output normal vectors. The sparse image has valid node pointers only in the band [IsoLevelLow, IsoLevelHigh]. Pixels of the sparse image outside this band will be null pointers.

PARAMETERS

IsoLevelLow and IsoLevelHigh define the working band for this filter. Pixels of the input scalar image whose values fall between these low and high limits will be operated on. MaxIteration determines the number of iterations this filter will perform. (Default is 25) The MinVectorNorm parameter determines the minumum vector norm allowed (to avoid divide by 0). The default for MinVectorNorm is 10^-6 which is designed to work with an input image of floats. This value can be lowered to 10^-12 if the input image is doubles.

IMPORTANT

The TSparseOutputImage template parameter must be a sparse image templated over a NodeType which at least has the following members: m_Data, m_InputData, m_Update and m_MAnifoldNormal. Depending on the Function object being used it might need other members. For instance, NormalVectorDiffusionFunction will also require that the NodeType has the following additional members: m_Flux.

Definition at line 71 of file itkImplicitManifoldNormalVectorFilter.h.

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef DataObject::Pointer	DataObjectPointer
typedef std::vector< DataObjectPointer >	DataObjectPointerArray
typedef Superclass::FiniteDifferenceFunctionType	FiniteDifferenceFunctionType
typedef Superclass::IndexType	IndexType
typedef InputImageType::ConstPointer	InputImageConstPointer
typedef ConstNeighborhoodIterator< InputImageType >	InputImageIteratorType
typedef InputImageType::PixelType	InputImagePixelType
typedef InputImageType::Pointer	InputImagePointer
typedef InputImageType::RegionType	InputImageRegionType
typedef Superclass::InputImageType	InputImageType
typedef OutputNodeType::NodeDataType	NodeDataType
typedef Superclass::NodeListType	NodeListType
typedef Superclass::NodeValueType	NodeValueType
typedef Superclass::OutputNodeType	NormalBandNodeType
typedef NormalVectorFunctionBase< SparseOutputImageType >	NormalFunctionType
typedef Superclass::NodeDataType	NormalVectorType
typedef Superclass::OutputImagePixelType	OutputImagePixelType
typedef Superclass::OutputImagePointer	OutputImagePointer
typedef Superclass::OutputImageRegionType	OutputImageRegionType
typedef TSparseOutputImage	OutputImageType
typedef SparseOutputImageType::NodeType	OutputNodeType
typedef Superclass::PixelType	PixelType
typedef SmartPointer< Self >	Pointer
typedef FiniteDifferenceFunctionType::RadiusType	RadiusType
typedef ImplicitManifoldNormalVectorFilter	Self
typedef FiniteDifferenceSparseImageFunction< SparseOutputImageType >	SparseFunctionType
typedef Superclass::SparseOutputImageType	SparseOutputImageType
typedef FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >	Superclass
typedef Superclass::TimeStepType	TimeStepType
Public Member Functions
virtual void	AbortGenerateDataOff ()
virtual void	AbortGenerateDataOn ()
Can the filter run in place To do the filter s first input *and output must have the same dimension and pixel type This *method can be used in conjunction with the InPlace ivar to *determine whether a particular use of the filter is really *running in place Some filters may be able to optimize their *operation if the InPlace is true and CanRunInPlace is true *bool	CanRunInPlace () const
virtual LightObject::Pointer	CreateAnother () const
virtual void	DebugOff () const
virtual void	DebugOn () const
virtual void	Delete ()
virtual void	EnlargeOutputRequestedRegion (DataObject *)
virtual const bool &	GetAbortGenerateData ()
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
virtual const FiniteDifferenceFunctionType::Pointer &	GetDifferenceFunction () const
virtual const unsigned int &	GetElapsedIterations ()
virtual bool	GetInPlace ()
const InputImageType *	GetInput (unsigned int idx)
const InputImageType *	GetInput (void)
DataObjectPointerArray &	GetInputs ()
virtual NodeValueType	GetIsoLevelHigh ()
virtual NodeValueType	GetIsoLevelLow ()
virtual const double &	GetMaximumRMSError ()
virtual unsigned int	GetMaxIteration ()
const MetaDataDictionary &	GetMetaDataDictionary (void) const
MetaDataDictionary &	GetMetaDataDictionary (void)
virtual NodeValueType	GetMinVectorNorm ()
virtual unsigned long	GetMTime () const
MultiThreader *	GetMultiThreader ()
virtual const char *	GetNameOfClass () const
std::vector< DataObjectPointer >::size_type	GetNumberOfInputs () const
virtual const unsigned int &	GetNumberOfIterations ()
std::vector< DataObjectPointer >::size_type	GetNumberOfOutputs () const
virtual const int &	GetNumberOfThreads ()
virtual std::vector< DataObjectPointer >::size_type	GetNumberOfValidRequiredInputs () const
OutputImageType *	GetOutput (unsigned int idx)
Get the output data of this process object The output of this *function is not valid until an appropriate either explicitly or implicitly Both the filter *itself and the data object have and both *methods update the data Here are three ways to use *	GetOutput () and make sure the data is valid.In these *examples
Return an array with all the outputs of this process object *This is useful for tracing forward in the pipeline to contruct *graphs etc *DataObjectPointerArray &	GetOutputs ()
virtual bool	GetPrecomputeFlag ()
virtual const float &	GetProgress ()
virtual int	GetReferenceCount () const
virtual const bool &	GetReleaseDataBeforeUpdateFlag ()
virtual bool	GetReleaseDataFlag () const
virtual const double &	GetRMSChange ()
virtual const FilterStateType &	GetState ()
virtual bool	GetUnsharpMaskingFlag ()
virtual NodeValueType	GetUnsharpMaskingWeight ()
virtual const bool &	GetUseImageSpacing ()
virtual void	GraftNthOutput (unsigned int idx, DataObject *output)
virtual void	GraftOutput (DataObject *output)
This is the stopping criterion function used in the iterative finite difference scheme *virtual bool	Halt ()
bool	HasObserver (const EventObject &event) const
Get the output data of this process object The output of this *function is not valid until an appropriate either explicitly or implicitly Both the filter *itself and the data object have and both *methods update the data Here are three ways to use *a image is a pointer to some Image and the *particular ProcessObjects involved are filters The same *examples apply to non	image (e.g.Mesh) data as well.**\code *anotherFilter->SetInput(someFilter->GetOutput())
virtual void	InPlaceOff ()
virtual void	InPlaceOn ()
void	InvokeEvent (const EventObject &) const
void	InvokeEvent (const EventObject &)
	itkStaticConstMacro (OutputImageDimension, unsigned int, TSparseOutputImage::ImageDimension)
ImageDimension constants *	itkStaticConstMacro (InputImageDimension, unsigned int, TInputImage::ImageDimension)
	itkStaticConstMacro (ImageDimension, unsigned int, OutputImageType::ImageDimension)
	itkStaticConstMacro (ImageDimension, unsigned int, Superclass::ImageDimension)
virtual DataObjectPointer	MakeOutput (unsigned int idx)
virtual void	Modified () const
virtual void	PopBackInput ()
virtual void	PopFrontInput ()
virtual void	PrepareOutputs ()
void	Print (std::ostream &os, Indent indent=0) const
virtual void	PropagateRequestedRegion (DataObject *output)
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 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 if an application has *images and they need to run a filter on then *run the filter on then run the filter on 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 this only makes sense for *filters that single type of input **Other uses are also possible For a single input pushing *and popping inputs allow the application to temporarily replace *an input to a filter **virtual void	PushBackInput (const InputImageType *image)
virtual void	PushFrontInput (const InputImageType *image)
virtual void	Register () const
virtual void	ReleaseDataBeforeUpdateFlagOff ()
virtual void	ReleaseDataBeforeUpdateFlagOn ()
void	ReleaseDataFlagOff ()
void	ReleaseDataFlagOn ()
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
virtual void	ResetPipeline ()
virtual void	SetAbortGenerateData (bool _arg)
void	SetDebug (bool debugFlag) const
virtual void	SetDifferenceFunction (FiniteDifferenceFunctionType *_arg)
In place operation can be turned on and off This only has an *effect when the input and output image type match *virtual void	SetInPlace (bool _arg)
virtual void	SetInput (unsigned int, const TInputImage *image)
Set Get the image input of this process object *virtual void	SetInput (const InputImageType *image)
virtual void	SetIsoLevelHigh (NodeValueType _arg)
virtual void	SetIsoLevelLow (NodeValueType _arg)
Set Get the maximum error allowed in the solution This may not be defined for all solvers and its meaning may change with the application *virtual void	SetMaximumRMSError (double _arg)
virtual void	SetMaxIteration (unsigned int _arg)
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
virtual void	SetMinVectorNorm (NodeValueType _arg)
void	SetNormalFunction (NormalFunctionType *nf)
Set Get the number of iterations that the filter will run *virtual void	SetNumberOfIterations (unsigned int _arg)
Get Set the number of threads to create when executing *virtual void	SetNumberOfThreads (int _arg)
virtual void	SetPrecomputeFlag (bool _arg)
virtual void	SetProgress (float _arg)
virtual void	SetReferenceCount (int)
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 *virtual void	SetReleaseDataFlag (bool flag)
Set Get the root mean squared change of the previous iteration May not be used by all solvers *virtual void	SetRMSChange (double _arg)
void	SetSparseFunction (SparseFunctionType *sf)
Set Get the state of the filter *virtual void	SetState (FilterStateType _arg)
void	SetStateToInitialized ()
void	SetStateToUninitialized ()
virtual void	SetUnsharpMaskingFlag (bool _arg)
virtual void	SetUnsharpMaskingWeight (NodeValueType _arg)
Use the image spacing information in calculations Use this option if you *want derivatives in physical space Default is UseImageSpacingOff *virtual void	SetUseImageSpacing (bool _arg)
virtual void	UnRegister () const
*endcode *In the above the two lines of code can be in *either order **Note that it may be more efficient to *use a pipeline than to call	Update () once for each filter in *turn.**For an image
*endcode *In the above 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\b streaming(using a *StreamingImageFilter) is activated
*endcode **code *someFilter	Update ()
*image	Update ()
*anotherFilter	Update ()
Get the output data of this process object The output of this *function is not valid until an appropriate either explicitly or implicitly Both the filter *itself and the data object have	Update () methods
Get the output data of this process object The output of this *function is not valid until an appropriate	Update () method has *been called
virtual void	UpdateLargestPossibleRegion ()
virtual void	UpdateOutputData (DataObject *output)
virtual void	UpdateOutputInformation ()
void	UpdateProgress (float amount)
virtual void	UseImageSpacingOff ()
virtual void	UseImageSpacingOn ()
Static Public Member Functions
static void	BreakOnError ()
static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static Pointer	New ()
This is a global flag that controls whether any warning *or error messages are displayed *static void	SetGlobalWarningDisplay (bool flag)
Public Attributes
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 unsigned lon	AddObserver )(const EventObject &event, Command *) const
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 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 if an application has *images and they need to run a filter on then *run the filter on then run the filter on 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 is a global flag that controls whether any	debug
*endcode *In the above	example
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 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 if an application has *images and they need to run a filter on then *run the filter on then run the filter on 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 this only makes sense for *filters that single type of input **Other uses are also possible For a single input	filter
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
*	image
*endcode **In this a someFilter and a anotherFilter are said *to constitute a b pipeline **code *	image
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 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 if an application has *images and they need to run a filter on then *run the filter on then run the filter on *	images
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 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 if an application has *images and they need to run a filter on then *run the filter on	images
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 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 if an application has *images and they need to run a filter on	images
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 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
Get the output data of this process object The output of this *function is not valid until an appropriate either explicitly or implicitly Both the filter *itself and the data object have and both *methods update the data Here are three ways to use *a image is a pointer to some Image	object
*endcode *In the above the two lines of code can be in *either order **Note that it may be more efficient to *use a pipeline than to call the data generated is for the requested *	Region
*endcode **In this	situation
Can the filter run in place To do	so
Protected Types
typedef ImageToImageFilterDetail::ImageRegionCopier< itkGetStaticConstMacro(OutputImageDimension), itkGetStaticConstMacro(InputImageDimension)	InputToOutputRegionCopierType )
typedef ImageToImageFilterDetail::ImageRegionCopier< itkGetStaticConstMacro(InputImageDimension), itkGetStaticConstMacro(OutputImageDimension)	OutputToInputRegionCopierType )
Protected Member Functions
virtual void	AddInput (DataObject *input)
virtual void	AddOutput (DataObject *output)
virtual void	AfterThreadedGenerateData ()
virtual void	AllocateOutputs ()
virtual void	AllocateUpdateBuffer ()
virtual void	ApplyUpdate (TimeStepType dt)
virtual void	BeforeThreadedGenerateData ()
virtual void	CacheInputReleaseDataFlags ()
virtual TimeStepType	CalculateChange ()
virtual void	CallCopyInputRegionToOutputRegion (OutputImageRegionType &destRegion, const InputImageRegionType &srcRegion)
virtual void	CallCopyOutputRegionToInputRegion (InputImageRegionType &destRegion, const OutputImageRegionType &srcRegion)
virtual void	CopyInputToOutput ()
virtual NodeDataType	DataConstraint (const NodeDataType &data) const
virtual NormalVectorType	DataConstraint (const NormalVectorType &data) const
	FiniteDifferenceSparseImageFilter ()
virtual void	GenerateData ()
virtual void	GenerateInputRequestedRegion ()
virtual void	GenerateOutputInformation ()
virtual void	GenerateOutputRequestedRegion (DataObject *output)
const DataObject *	GetInput (unsigned int idx) const
virtual const unsigned int &	GetNumberOfRequiredInputs ()
virtual const unsigned int &	GetNumberOfRequiredOutputs ()
const DataObject *	GetOutput (unsigned int idx) const
int	GetSplitRegion (int i, int num, ThreadRegionType &splitRegion)
	ImageSource ()
	ImageToImageFilter ()
	ImplicitManifoldNormalVectorFilter ()
virtual void	Initialize ()
void	InitializeNormalBandNode (NormalBandNodeType *node, const InputImageIteratorType &it)
	InPlaceImageFilter ()
virtual void	PostProcessOutput ()
virtual void	PrecalculateChange ()
bool	PrintObservers (std::ostream &os, Indent indent) const
void	PrintSelf (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const
virtual void	PropagateResetPipeline ()
**these methods end of hiding the versions from the superclass *ProcessObject whose arguments are DataObjects we re expose *the versions from ProcessObject to avoid warnings about hiding *methods from the superclass *void	PushBackInput (const DataObject *input)
*	PushBackInput ()
*	PushFronInput () in the public section force the *input to be the type expected by an ImageToImageFilter.However
void	PushFrontInput (const DataObject *input)
virtual void	ReleaseInputs ()
virtual void	RemoveInput (DataObject *input)
virtual void	RemoveOutput (DataObject *output)
virtual void	RestoreInputReleaseDataFlags ()
void	SetNormalBand ()
Protected methods for setting inputs *Subclasses make use of them for setting input *virtual void	SetNthInput (unsigned int num, DataObject *input)
Protected methods for setting outputs *Subclasses make use of them for getting output *virtual void	SetNthOutput (unsigned int num, DataObject *output)
void	SetNumberOfInputs (unsigned int num)
void	SetNumberOfOutputs (unsigned int num)
virtual void	SetNumberOfRequiredInputs (unsigned int _arg)
virtual void	SetNumberOfRequiredOutputs (unsigned int _arg)
virtual int	SplitRequestedRegion (int i, int num, OutputImageRegionType &splitRegion)
virtual void	ThreadedApplyUpdate (TimeStepType dt, const ThreadRegionType &regionToProcess, int threadId)
virtual TimeStepType	ThreadedCalculateChange (const ThreadRegionType &regionToProcess, int threadId)
virtual void	ThreadedGenerateData (const OutputImageRegionType &outputRegionForThread, int threadId)
virtual void	ThreadedPrecalculateChange (const ThreadRegionType &regionToProcess, int threadId)
	~ImplicitManifoldNormalVectorFilter ()
Static Protected Member Functions
Multi threaded implementation of ApplyUpdate *static ITK_THREAD_RETURN_TYPE	ApplyUpdateThreaderCallback (void *arg)
Multuthreaded implementation of CalculateChange *static ITK_THREAD_RETURN_TYPE	CalculateChangeThreaderCallback (void *arg)
Multithreaded implementation of PrecalculateChange *static ITK_THREAD_RETURN_TYPE	PrecalculateChangeThreaderCallback (void *arg)
static ITK_THREAD_RETURN_TYPE	ThreaderCallback (void *arg)
Protected Attributes
**these methods end of hiding the versions from the superclass *ProcessObject whose arguments are DataObjects	Here
TimeStamp	m_OutputInformationMTime
int	m_ReferenceCount
SimpleFastMutexLock	m_ReferenceCountLock
bool	m_Updating
Methods invoked by virtual 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 PrintSelf(std voi	PrintHeader )(std::ostream &os, Indent indent) const

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Member Typedef Documentation

template<class TInputImage, class TSparseOutputImage> typedef SmartPointer<const Self> itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::ConstPointer

Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 81 of file itkImplicitManifoldNormalVectorFilter.h.

typedef DataObject::Pointer itk::ImageSource< TSparseOutputImage >::DataObjectPointer [inherited]

Smart Pointer type to a DataObject. Reimplemented from itk::ProcessObject. Definition at line 62 of file itkImageSource.h.

typedef std::vector<DataObjectPointer> itk::ProcessObject::DataObjectPointerArray [inherited]

STL Array of SmartPointers to DataObjects Definition at line 103 of file itkProcessObject.h.

template<class TInputImage, class TSparseOutputImage> typedef Superclass::FiniteDifferenceFunctionType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::FiniteDifferenceFunctionType

The value type of the time step. This is distinct from PixelType because PixelType may often be a vector value, while the TimeStep is a scalar value. Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 99 of file itkImplicitManifoldNormalVectorFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef Superclass::IndexType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::IndexType

Typedefs from the sparse output image type. Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 95 of file itkImplicitManifoldNormalVectorFilter.h.

typedef InputImageType::ConstPointer itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::InputImageConstPointer [inherited]

Reimplemented from itk::ImageToImageFilter< TInputImage, TSparseOutputImage >. Definition at line 84 of file itkInPlaceImageFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef ConstNeighborhoodIterator<InputImageType> itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::InputImageIteratorType

The iterator for the input image. Definition at line 105 of file itkImplicitManifoldNormalVectorFilter.h.

typedef InputImageType::PixelType itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::InputImagePixelType [inherited]

Reimplemented from itk::ImageToImageFilter< TInputImage, TSparseOutputImage >. Definition at line 86 of file itkInPlaceImageFilter.h.

typedef InputImageType::Pointer itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::InputImagePointer [inherited]

Reimplemented from itk::ImageToImageFilter< TInputImage, TSparseOutputImage >. Definition at line 83 of file itkInPlaceImageFilter.h.

typedef InputImageType::RegionType itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::InputImageRegionType [inherited]

Reimplemented from itk::ImageToImageFilter< TInputImage, TSparseOutputImage >. Definition at line 85 of file itkInPlaceImageFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef Superclass::InputImageType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::InputImageType

Typedefs from the superclass Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 94 of file itkImplicitManifoldNormalVectorFilter.h.

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

Typedef for the region copier function object that converts an input region to an output region. Definition at line 163 of file itkImageToImageFilter.h.

typedef OutputNodeType::NodeDataType itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::NodeDataType [inherited]

The type for the data variable of OutputNodeType. Definition at line 95 of file itkFiniteDifferenceSparseImageFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef Superclass::NodeListType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::NodeListType

Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 102 of file itkImplicitManifoldNormalVectorFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef Superclass::NodeValueType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::NodeValueType

The basic scalar variable type used in OutputNodeType. Expected to be float or double. If NodeDataType is a scalar, then this is the same type as that. Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 97 of file itkImplicitManifoldNormalVectorFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef Superclass::OutputNodeType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::NormalBandNodeType

Definition at line 101 of file itkImplicitManifoldNormalVectorFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef NormalVectorFunctionBase<SparseOutputImageType> itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::NormalFunctionType

This is the finite difference function type for processing the normal vectors Definition at line 109 of file itkImplicitManifoldNormalVectorFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef Superclass::NodeDataType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::NormalVectorType

Definition at line 96 of file itkImplicitManifoldNormalVectorFilter.h.

typedef Superclass::OutputImagePixelType itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::OutputImagePixelType [inherited]

Reimplemented from itk::ImageSource< TSparseOutputImage >. Definition at line 79 of file itkInPlaceImageFilter.h.

typedef Superclass::OutputImagePointer itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::OutputImagePointer [inherited]

Reimplemented from itk::ImageSource< TSparseOutputImage >. Definition at line 77 of file itkInPlaceImageFilter.h.

typedef Superclass::OutputImageRegionType itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::OutputImageRegionType [inherited]

Superclass typedefs. Reimplemented from itk::ImageToImageFilter< TInputImage, TSparseOutputImage >. Definition at line 78 of file itkInPlaceImageFilter.h.

typedef TSparseOutputImage itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::OutputImageType [inherited]

Superclass typedefs. Reimplemented from itk::InPlaceImageFilter< TInputImage, TSparseOutputImage >. Definition at line 138 of file itkFiniteDifferenceImageFilter.h.

typedef SparseOutputImageType::NodeType itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::OutputNodeType [inherited]

Definition at line 91 of file itkFiniteDifferenceSparseImageFilter.h.

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

Typedef for the region copier function object that converts an output region to an input region. Definition at line 168 of file itkImageToImageFilter.h.

typedef Superclass::PixelType itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::PixelType [inherited]

The pixel type of the output image will be used in computations. Reimplemented from itk::FiniteDifferenceImageFilter< TInputImage, TSparseOutputImage >. Definition at line 79 of file itkFiniteDifferenceSparseImageFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef SmartPointer<Self> itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::Pointer

Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 80 of file itkImplicitManifoldNormalVectorFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef FiniteDifferenceFunctionType::RadiusType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::RadiusType

This is the radius type for the image neigborhoods. Definition at line 112 of file itkImplicitManifoldNormalVectorFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef ImplicitManifoldNormalVectorFilter itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::Self

Standard class typedef Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 77 of file itkImplicitManifoldNormalVectorFilter.h.

typedef FiniteDifferenceSparseImageFunction<SparseOutputImageType> itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::SparseFunctionType [inherited]

The sparse image finite difference function type used in this class. Definition at line 104 of file itkFiniteDifferenceSparseImageFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef Superclass::SparseOutputImageType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SparseOutputImageType

Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 100 of file itkImplicitManifoldNormalVectorFilter.h.

template<class TInputImage, class TSparseOutputImage> typedef FiniteDifferenceSparseImageFilter<TInputImage, TSparseOutputImage> itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::Superclass

Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >. Definition at line 79 of file itkImplicitManifoldNormalVectorFilter.h.

typedef Superclass::TimeStepType itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::TimeStepType [inherited]

Reimplemented from itk::FiniteDifferenceImageFilter< TInputImage, TSparseOutputImage >. Definition at line 80 of file itkFiniteDifferenceSparseImageFilter.h.

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Constructor & Destructor Documentation

template<class TInputImage, class TSparseOutputImage> itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::ImplicitManifoldNormalVectorFilter (   )  [protected]

template<class TInputImage, class TSparseOutputImage> itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::~ImplicitManifoldNormalVectorFilter (   )  [inline, protected]

Definition at line 132 of file itkImplicitManifoldNormalVectorFilter.h.

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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]

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

virtual void itk::ImageSource< TSparseOutputImage >::AfterThreadedGenerateData (   )  [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 254 of file itkImageSource.h.

virtual void itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::AllocateOutputs (   )  [protected, virtual, inherited]

The GenerateData method normally allocates the buffers for all of the outputs of a filter. Since InPlaceImageFilter's can use an overwritten version of the input for its output, the output buffer should not be allocated. When possible, we graft the input to the filter to the output. If an InPlaceFilter has multiple outputs, then it would need to override this method to graft one of its outputs and allocate the remaining. If a filter is threaded (i.e. it provides an implementation of ThreadedGenerateData()), this method is called automatically. If an InPlaceFilter is not threaded (i.e. it provides an implementation of GenerateData()), then this method (or equivalent) must be called in GenerateData(). Reimplemented from itk::ImageSource< TSparseOutputImage >.

virtual void itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::AllocateUpdateBuffer (   )  [inline, protected, virtual, inherited]

This class does not use AllocateUpdateBuffer to allocate memory for its narrow band. All memory is handled through the SparseImage class. Definition at line 124 of file itkFiniteDifferenceSparseImageFilter.h.

virtual void itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::ApplyUpdate (  TimeStepType  dt  )  [protected, virtual, inherited]

This function updates the m_Data variable in the output image nodes using the update values computed by CalculateChange.

Multi threaded implementation of ApplyUpdate* static ITK_THREAD_RETURN_TYPE itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::ApplyUpdateThreaderCallback (  void *  arg  )  [static, protected, inherited]

virtual void itk::ImageSource< TSparseOutputImage >::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 242 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 TimeStepType itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::CalculateChange (   )  [protected, virtual, inherited]

This method computes changes to the output image using the ComputeSparseUpdate method in the Sparse Function object.

Multuthreaded implementation of CalculateChange* static ITK_THREAD_RETURN_TYPE itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::CalculateChangeThreaderCallback (  void *  arg  )  [static, protected, inherited]

virtual void itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::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 , TSparseOutputImage >::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).

Can the filter run in place To do the filter s first input* and output must have the same dimension and pixel type This* method can be used in conjunction with the InPlace ivar to* determine whether a particular use of the filter is really* running in place Some filters may be able to optimize their* operation if the InPlace is true and CanRunInPlace is true* bool itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::CanRunInPlace (   )  const [inline, inherited]

Definition at line 108 of file itkInPlaceImageFilter.h.

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::CopyInputToOutput (   )  [inline, protected, virtual]

This function does nothing. The output initialization is handled by Initialize. Definition at line 147 of file itkImplicitManifoldNormalVectorFilter.h.

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

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

virtual NodeDataType itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::DataConstraint (  const NodeDataType &  data  )  const [inline, protected, virtual, inherited]

This function can be used to implements constraints on the range of data values. Default is no constraint. Definition at line 128 of file itkFiniteDifferenceSparseImageFilter.h.

template<class TInputImage, class TSparseOutputImage> virtual NormalVectorType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::DataConstraint (  const NormalVectorType &  data  )  const [inline, protected, virtual]

This function implements the unit norm constraint for normal vectors. Definition at line 181 of file itkImplicitManifoldNormalVectorFilter.h.

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.

virtual void itk::ProcessObject::EnlargeOutputRequestedRegion (  DataObject *   )  [inline, virtual, inherited]

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 in itk::CurvatureFlowImageFilter< TInputImage, TOutputImage >, itk::ExtensionVelocitiesImageFilter< TLevelSet, TAuxValue, VAuxDimension >, itk::FastMarchingExtensionImageFilter< TLevelSet, TAuxValue, VAuxDimension, TSpeedImage >, itk::FastMarchingImageFilter< TLevelSet, TSpeedImage >, itk::ImagePCAShapeModelEstimator< TInputImage, TOutputImage >, itk::IsoContourDistanceImageFilter< TInputImage, TOutputImage >, itk::IsolatedWatershedImageFilter< TInputImage, TOutputImage >, itk::KLMRegionGrowImageFilter< TInputImage, TOutputImage >, itk::MRFImageFilter< TInputImage, TClassifiedImage >, itk::MultiResolutionPDEDeformableRegistration< TFixedImage, TMovingImage, TDeformationField >, itk::ReinitializeLevelSetImageFilter< TLevelSet >, itk::VoronoiSegmentationImageFilterBase< TInputImage, TOutputImage, TBinaryPriorImage >, itk::WatershedImageFilter< TInputImage >, itk::BlackTopHatImageFilter< TInputImage, TOutputImage, TKernel >, itk::BSplineDecompositionImageFilter< TInputImage, TOutputImage >, itk::ClosingByReconstructionImageFilter< TInputImage, TOutputImage, TKernel >, itk::ConfidenceConnectedImageFilter< TInputImage, TOutputImage >, itk::ConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage >, itk::ConnectedThresholdImageFilter< TInputImage, TOutputImage >, itk::ContourDirectedMeanDistanceImageFilter< TInputImage1, TInputImage2 >, itk::ContourMeanDistanceImageFilter< TInputImage1, TInputImage2 >, itk::DirectedHausdorffDistanceImageFilter< TInputImage1, TInputImage2 >, itk::DoubleThresholdImageFilter< TInputImage, TOutputImage >, itk::ExtractOrthogonalSwath2DImageFilter< TImage >, itk::GradientMagnitudeRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::GradientRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::GrayscaleConnectedClosingImageFilter< TInputImage, TOutputImage >, itk::GrayscaleConnectedOpeningImageFilter< TInputImage, TOutputImage >, itk::GrayscaleFillholeImageFilter< TInputImage, TOutputImage >, itk::GrayscaleGeodesicDilateImageFilter< TInputImage, TOutputImage >, itk::GrayscaleGeodesicErodeImageFilter< TInputImage, TOutputImage >, itk::GrayscaleGrindPeakImageFilter< TInputImage, TOutputImage >, itk::GrayscaleMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >, itk::HausdorffDistanceImageFilter< TInputImage1, TInputImage2 >, itk::HConcaveImageFilter< TInputImage, TOutputImage >, itk::HConvexImageFilter< TInputImage, TOutputImage >, itk::HessianRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::HMaximaImageFilter< TInputImage, TOutputImage >, itk::HMinimaImageFilter< TInputImage, TOutputImage >, itk::HoughTransform2DCirclesImageFilter< TInputPixelType, TOutputPixelType >, itk::HoughTransform2DLinesImageFilter< TInputPixelType, TOutputPixelType >, itk::ImportImageFilter< TPixel, VImageDimension >, itk::IsolatedConnectedImageFilter< TInputImage, TOutputImage >, itk::LabelStatisticsImageFilter< TInputImage, TLabelImage >, itk::LaplacianRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::MinimumMaximumImageFilter< TInputImage >, itk::NeighborhoodConnectedImageFilter< TInputImage, TOutputImage >, itk::OpeningByReconstructionImageFilter< TInputImage, TOutputImage, TKernel >, itk::OrientImageFilter< TInputImage, TOutputImage >, itk::ReconstructionByDilationImageFilter< TInputImage, TOutputImage >, itk::ReconstructionByErosionImageFilter< TInputImage, TOutputImage >, itk::RecursiveSeparableImageFilter< TInputImage, TOutputImage >, itk::RegionOfInterestImageFilter< TInputImage, TOutputImage >, itk::SimilarityIndexImageFilter< TInputImage1, TInputImage2 >, itk::SmoothingRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::StatisticsImageFilter< TInputImage >, itk::TobogganImageFilter< TInputImage >, itk::VectorConfidenceConnectedImageFilter< TInputImage, TOutputImage >, itk::WhiteTopHatImageFilter< TInputImage, TOutputImage, TKernel >, itk::ImageFileReader< TOutputImage, ConvertPixelTraits >, itk::ImageSeriesReader< TOutputImage >, and itk::VoronoiSegmentationImageFilterBase< TInputImage, TOutputImage >. Definition at line 222 of file itkProcessObject.h.

itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::FiniteDifferenceSparseImageFilter (   )  [protected, inherited]

virtual void itk::ImageSource< TSparseOutputImage >::GenerateData (  void   )  [protected, virtual, inherited]

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::ProcessObject.

virtual void itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::GenerateInputRequestedRegion (   )  [protected, virtual, inherited]

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::ProcessObject.

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

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 in itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >, itk::BinaryMask3DMeshSource< TInputImage, TOutputMesh >, itk::FastMarchingExtensionImageFilter< TLevelSet, TAuxValue, VAuxDimension, TSpeedImage >, itk::FastMarchingImageFilter< TLevelSet, TSpeedImage >, itk::FFTComplexConjugateToRealImageFilter< TPixel, Dimension >, itk::FFTRealToComplexConjugateImageFilter< TPixel, Dimension >, itk::MRFImageFilter< TInputImage, TClassifiedImage >, itk::MultiResolutionPDEDeformableRegistration< TFixedImage, TMovingImage, TDeformationField >, itk::MultiResolutionPyramidImageFilter< TInputImage, TOutputImage >, itk::PDEDeformableRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >, itk::VoronoiDiagram2DGenerator< TCoordType >, itk::AccumulateImageFilter< TInputImage, TOutputImage >, itk::BinaryMaskToNarrowBandPointSetFilter< TInputImage, TOutputMesh >, itk::ChangeInformationImageFilter< TInputImage >, itk::CropImageFilter< TInputImage, TOutputImage >, itk::DeformationFieldSource< TOutputImage >, itk::ExpandImageFilter< TInputImage, TOutputImage >, itk::ExtractImageFilter< TInputImage, TOutputImage >, itk::ExtractOrthogonalSwath2DImageFilter< TImage >, itk::FlipImageFilter< TImage >, itk::GaussianImageSource< TOutputImage >, itk::GradientImageToBloxBoundaryPointImageFilter< TInputImage >, itk::HoughTransform2DLinesImageFilter< TInputPixelType, TOutputPixelType >, itk::ImageToMeshFilter< TInputImage, TOutputMesh >, itk::ImageToParametricSpaceFilter< TInputImage, TOutputMesh >, itk::ImportImageFilter< TPixel, VImageDimension >, itk::InterpolateImagePointsFilter< TInputImage, TOutputImage, TCoordType, InterpolatorType >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::JoinSeriesImageFilter< TInputImage, TOutputImage >, itk::NonThreadedShrinkImageFilter< TInputImage, TOutputImage >, itk::OrientImageFilter< TInputImage, TOutputImage >, itk::PadImageFilter< TInputImage, TOutputImage >, itk::ParametricSpaceToImageSpaceMeshFilter< TInputMesh, TOutputMesh >, itk::PathToImageFilter< TInputPath, TOutputImage >, itk::PermuteAxesImageFilter< TImage >, itk::PointSetToImageFilter< TInputPointSet, TOutputImage >, itk::RandomImageSource< TOutputImage >, itk::RegionOfInterestImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::ShrinkImageFilter< TInputImage, TOutputImage >, itk::SpatialObjectToImageFilter< TInputSpatialObject, TOutputImage >, itk::SpatialObjectToPointSetFilter< TInputSpatialObject, TOutputPointSet >, itk::TileImageFilter< TInputImage, TOutputImage >, itk::TriangleMeshToBinaryImageFilter, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, TFunction >, itk::VectorExpandImageFilter< TInputImage, TOutputImage >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VTKImageImport< TOutputImage >, itk::WarpImageFilter< TInputImage, TOutputImage, TDeformationField >, itk::WarpVectorImageFilter< TInputImage, TOutputImage, TDeformationField >, itk::ImageFileReader< TOutputImage, ConvertPixelTraits >, itk::ImageSeriesReader< TOutputImage >, itk::HistogramToImageFilter< THistogram, TFunction >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Atan< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Cos< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Acos< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::InvertIntensityTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::ChangeLabel< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< FeatureImageType, ImageType, Functor::Cast< FeatureImageType::PixelType, ImageType::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Log< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Abs< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Exp< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ComplexToReal< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Cast< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::BoundedReciprocal< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Sigmoid< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::VectorCast< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::VectorMagnitudeLinearTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::IntensityLinearTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ComplexToModulus< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::IntensityWindowingTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::NOT< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Tan< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ExpNegative< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ComplexToPhase< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::ThresholdLabeler< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::SymmetricEigenAnalysisFunction< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Sin< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::RGBToLuminance< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::TensorRelativeAnisotropyFunction< TInputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::MatrixIndexSelection< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Sqrt< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::BinaryThreshold< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Log10< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::AccessorFunctor< TInputImage::PixelType, TAccessor > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::ModulusTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::TensorFractionalAnisotropyFunction< TInputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Asin< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::EdgePotential< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Square< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::VectorIndexSelectionCast< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::GradientMagnitude< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ComplexToImaginary< TInputImage::PixelType, TOutputImage::PixelType > >, itk::HistogramToImageFilter< THistogram, Function::HistogramEntropyFunction< unsigned long > >, itk::HistogramToImageFilter< THistogram, Function::HistogramLogProbabilityFunction< unsigned long > >, itk::HistogramToImageFilter< THistogram, Function::HistogramProbabilityFunction< unsigned long > >, and itk::HistogramToImageFilter< THistogram, Function::HistogramIntensityFunction< unsigned long > >.

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)>, 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.

virtual const FiniteDifferenceFunctionType ::Pointer& itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::GetDifferenceFunction (   )  const [virtual, inherited]

This method returns a pointer to a FiniteDifferenceFunction object that will be used by the filter to calculate updates at image pixels. Returns: A FiniteDifferenceObject pointer.

virtual const unsigned int& itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::GetElapsedIterations (   )  [virtual, inherited]

Get the number of elapsed iterations of the filter.

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

virtual bool itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::GetInPlace (   )  [virtual, inherited]

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

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

Reimplemented from itk::ProcessObject.

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

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 TSparseOutputImage> virtual NodeValueType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::GetIsoLevelHigh (   )  [virtual]

template<class TInputImage, class TSparseOutputImage> virtual NodeValueType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::GetIsoLevelLow (   )  [virtual]

virtual const double& itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::GetMaximumRMSError (   )  [virtual, inherited]

template<class TInputImage, class TSparseOutputImage> virtual unsigned int itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::GetMaxIteration (   )  [virtual]

const MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  const [inherited]

Returns: A constant reference to this objects MetaDataDictionary.

MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  [inherited]

Returns: A reference to this objects MetaDataDictionary. Warning: This reference may be changed.

template<class TInputImage, class TSparseOutputImage> virtual NodeValueType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::GetMinVectorNorm (   )  [virtual]

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

Return this objects modified time. Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::SceneSpatialObject< SpaceDimension >, and itk::SceneSpatialObject< NDimensions >.

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

Return the multithreader used by this class. Definition at line 281 of file itkProcessObject.h.

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

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

std::vector<DataObjectPointer>::size_type 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 115 of file itkProcessObject.h.

virtual const unsigned int& itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::GetNumberOfIterations (   )  [virtual, inherited]

std::vector<DataObjectPointer>::size_type itk::ProcessObject::GetNumberOfOutputs (   )  const [inline, inherited]

Definition at line 132 of file itkProcessObject.h.

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

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

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

virtual std::vector<DataObjectPointer>::size_type 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 >, and itk::PDEDeformableRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >.

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

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

Reimplemented from itk::ProcessObject.

Get the output data of this process object The output of this* function is not valid until an appropriate either explicitly or implicitly Both the filter* itself and the data object have and both* methods update the data Here are three ways to use* itk::ImageSource< TSparseOutputImage >::GetOutput (  void   )  [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* DataObjectPointerArray& itk::ProcessObject::GetOutputs (   )  [inline, inherited]

Definition at line 130 of file itkProcessObject.h.

virtual bool itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::GetPrecomputeFlag (   )  [virtual, inherited]

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.

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

Gets the reference count on this object. Definition at line 98 of file itkLightObject.h.

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

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

virtual const double& itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::GetRMSChange (   )  [virtual, inherited]

int itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::GetSplitRegion (  int  i, int  num, ThreadRegionType &  splitRegion )  [protected, inherited]

This function returns a single region for use in multi-threading.

virtual const FilterStateType& itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::GetState (   )  [virtual, inherited]

template<class TInputImage, class TSparseOutputImage> virtual bool itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::GetUnsharpMaskingFlag (   )  [virtual]

template<class TInputImage, class TSparseOutputImage> virtual NodeValueType itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::GetUnsharpMaskingWeight (   )  [virtual]

virtual const bool& itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::GetUseImageSpacing (   )  [virtual, inherited]

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

Definition at line 100 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

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

Definition at line 98 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

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

Graft the specified data object onto this ProcessObject's idx'th output. This is the similar to GraftOutput method except is allows you 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< TSparseOutputImage >::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).

template<class TInputImage, class TSparseOutputImage> This is the stopping criterion function used in the iterative finite difference scheme* virtual bool itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::Halt (   )  [inline, virtual]

Definition at line 194 of file itkImplicitManifoldNormalVectorFilter.h. References itk::fem::this.

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

Return true if an observer is registered for this event.

Get the output data of this process object The output of this* function is not valid until an appropriate either explicitly or implicitly Both the filter* itself and the data object have and both* methods update the data Here are three ways to use* a image is a pointer to some Image and the* particular ProcessObjects involved are filters The same* examples apply to non itk::ImageSource< TSparseOutputImage >::image (  e.g.  Mesh  )  [inherited]

itk::ImageSource< TSparseOutputImage >::ImageSource (   )  [protected, inherited]

itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::ImageToImageFilter (   )  [protected, inherited]

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::Initialize (   )  [protected, virtual]

This calls SetNormalBand to create the band of normals to process. Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >.

template<class TInputImage, class TSparseOutputImage> void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::InitializeNormalBandNode (  NormalBandNodeType *  node, const InputImageIteratorType &  it )  [protected]

This function precomputes information for normal vector processing .

itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::InPlaceImageFilter (   )  [protected, inherited]

virtual void itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::InPlaceOff (   )  [virtual, inherited]

virtual void itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::InPlaceOn (   )  [virtual, inherited]

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.

itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::itkStaticConstMacro (  OutputImageDimension  , unsigned  int, TSparseOutputImage ::ImageDimension  )  [inherited]

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

ImageDimension constants* itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::itkStaticConstMacro (  InputImageDimension  , unsigned  int, TInputImage ::ImageDimension  )  [inherited]

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

itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::itkStaticConstMacro (  ImageDimension  , unsigned  int, OutputImageType::ImageDimension  )  [inherited]

Dimensionality of input and output data is assumed to be the same.

template<class TInputImage, class TSparseOutputImage> itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::itkStaticConstMacro (  ImageDimension  , unsigned  int, Superclass::ImageDimension  )

Standard get dimension macro. Reimplemented from itk::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >.

virtual DataObjectPointer itk::ImageSource< TSparseOutputImage >::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.

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. Referenced by itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::HistogramAlgorithmBase< TInputHistogram >::SetInputHistogram(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints1(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints2(), itk::NonUniformBSpline< TDimension >::SetSplineOrder(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< typename ComponentType::HistogramType >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

template<class TInputImage, class TSparseOutputImage> static Pointer itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::New (   )  [static]

Standard New macro. Reimplemented from itk::Object.

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

Reimplemented from itk::ProcessObject.

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

Reimplemented from itk::ProcessObject.

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::PostProcessOutput (   )  [protected, virtual]

This function implements unsharp masking which is turned ON/OFF by the UnsharpMaskingFlag and controlled by the UnsharpMaskingWeight parameters.

virtual void itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::PrecalculateChange (   )  [protected, virtual, inherited]

This method provides a means of performing a first pass for computing the change and storing intermediate values that will then be used by CalculateChange. This can be used to speed up certain update rules.

Multithreaded implementation of PrecalculateChange* static ITK_THREAD_RETURN_TYPE itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::PrecalculateChangeThreaderCallback (  void *  arg  )  [static, protected, inherited]

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.

bool itk::Object::PrintObservers (  std::ostream &  os, Indent  indent )  const [protected, inherited]

template<class TInputImage, class TSparseOutputImage> void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::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::FiniteDifferenceSparseImageFilter< TInputImage, TSparseOutputImage >.

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

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::VTKImageImport< TOutputImage >.

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

Propagate a call to ResetPipeline() up the pipeline. Called only from DataObject.

* * these methods end of hiding the versions from the superclass* ProcessObject whose arguments are DataObjects we re expose* the versions from ProcessObject to avoid warnings about hiding* methods from the superclass* void itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::PushBackInput (  const DataObject *  input  )  [inline, protected, virtual, inherited]

Reimplemented from itk::ProcessObject. Definition at line 250 of file itkImageToImageFilter.h.

* itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::PushBackInput (   )  [protected, 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 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 if an application has* images and they need to run a filter on then* run the filter on then run the filter on 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 this only makes sense for* filters that single type of input* * Other uses are also possible For a single input pushing* and popping inputs allow the application to temporarily replace* an input to a filter** virtual void itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::PushBackInput (  const InputImageType *  image  )  [virtual, inherited]

* itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::PushFronInput (   )  [protected, inherited]

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

Reimplemented from itk::ProcessObject. Definition at line 252 of file itkImageToImageFilter.h.

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

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]

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

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

Definition at line 254 of file itkProcessObject.h.

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

Definition at line 253 of file itkProcessObject.h.

virtual void itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::ReleaseInputs (   )  [protected, virtual, inherited]

InPlaceImageFilter may transfer ownership of the input bulk data to the output object. Once the output object owns the bulk data (done in AllocateOutputs()), the input object must release its hold on the bulk data. ProcessObject::ReleaseInputs() only releases the input bulk data when the user has set the ReleaseDataFlag. InPlaceImageFilter::ReleaseInputs() also releases the input that it has overwritten. See also: ProcessObject::ReleaseInputs() Reimplemented from itk::ProcessObject.

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

Remove all observers .

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

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]

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.

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

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

virtual void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::SetDifferenceFunction (  FiniteDifferenceFunctionType *  _arg  )  [virtual, inherited]

This method sets the pointer to a FiniteDifferenceFunction object that will be used by the filter to calculate updates at image pixels. Returns: A FiniteDifferenceObject pointer.

This is a global flag that controls whether any warning* or error messages are displayed* static void itk::Object::SetGlobalWarningDisplay (  bool  flag  )  [static, inherited]

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

In place operation can be turned on and off This only has an* effect when the input and output image type match* virtual void itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::SetInPlace (  bool  _arg  )  [virtual, inherited]

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

Set Get the image input of this process object* virtual void itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::SetInput (  const InputImageType *  image  )  [virtual, inherited]

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SetIsoLevelHigh (  NodeValueType  _arg  )  [virtual]

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SetIsoLevelLow (  NodeValueType  _arg  )  [virtual]

Set Get the maximum error allowed in the solution This may not be defined for all solvers and its meaning may change with the application* virtual void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::SetMaximumRMSError (  double  _arg  )  [virtual, inherited]

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SetMaxIteration (  unsigned int  _arg  )  [virtual]

void itk::Object::SetMetaDataDictionary (  const MetaDataDictionary &  rhs  )  [inherited]

Returns: Set the MetaDataDictionary

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SetMinVectorNorm (  NodeValueType  _arg  )  [virtual]

template<class TInputImage, class TSparseOutputImage> void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SetNormalBand (   )  [protected]

This function sets the band for normal vector processing.

template<class TInputImage, class TSparseOutputImage> void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SetNormalFunction (  NormalFunctionType *  nf  )

This method is used to set the finite difference function.

Protected methods for setting inputs* Subclasses make use of them for setting input* virtual void itk::ProcessObject::SetNthInput (  unsigned int  num, DataObject *  input )  [protected, virtual, inherited]

Referenced by itk::watershed::BoundaryResolver< TPixelType, TDimension >::SetBoundaryA(), itk::watershed::BoundaryResolver< TPixelType, TDimension >::SetBoundaryB(), itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >::SetEquivalencyTable(), itk::WatershedImageFilter< TInputImage >::SetInput(), itk::watershed::SegmentTreeGenerator< ScalarType >::SetInputEquivalencyTable(), itk::watershed::Segmenter< TInputImage >::SetInputImage(), itk::watershed::Relabeler< ScalarType, itkGetStaticConstMacro(ImageDimension)>::SetInputImage(), itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >::SetInputImage(), itk::watershed::SegmentTreeGenerator< ScalarType >::SetInputSegmentTable(), itk::watershed::Relabeler< ScalarType, itkGetStaticConstMacro(ImageDimension)>::SetInputSegmentTree(), itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >::SetReferenceImage(), itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::SetReferenceImage(), and itk::ChangeInformationImageFilter< TInputImage >::SetReferenceImage().

Protected methods for setting outputs* Subclasses make use of them for getting output* virtual void itk::ProcessObject::SetNthOutput (  unsigned int  num, DataObject *  output )  [protected, virtual, inherited]

Referenced by itk::watershed::BoundaryResolver< TPixelType, TDimension >::BoundaryResolver(), itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >::EquivalenceRelabeler(), itk::watershed::Segmenter< TInputImage >::SetBoundary(), itk::watershed::BoundaryResolver< TPixelType, TDimension >::SetEquivalencyTable(), itk::watershed::Segmenter< TInputImage >::SetOutputImage(), itk::watershed::Relabeler< ScalarType, itkGetStaticConstMacro(ImageDimension)>::SetOutputImage(), itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >::SetOutputImage(), and itk::watershed::Segmenter< TInputImage >::SetSegmentTable().

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

Called to allocate the input array. Copies old inputs.

Set Get the number of iterations that the filter will run* virtual void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::SetNumberOfIterations (  unsigned int  _arg  )  [virtual, inherited]

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]

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

Get Set the number of threads to create when executing* virtual void itk::ProcessObject::SetNumberOfThreads (  int  _arg  )  [virtual, inherited]

virtual void itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::SetPrecomputeFlag (  bool  _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.

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

Set Get the root mean squared change of the previous iteration May not be used by all solvers* virtual void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::SetRMSChange (  double  _arg  )  [virtual, inherited]

void itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::SetSparseFunction (  SparseFunctionType *  sf  )  [inherited]

Sets the function object that will be called for computing updates.

Set Get the state of the filter* virtual void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::SetState (  FilterStateType  _arg  )  [virtual, inherited]

void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::SetStateToInitialized (   )  [inline, inherited]

Set the state of the filter to INITIALIZED Definition at line 195 of file itkFiniteDifferenceImageFilter.h.

void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::SetStateToUninitialized (   )  [inline, inherited]

Set the state of the filter to UNINITIALIZED Definition at line 201 of file itkFiniteDifferenceImageFilter.h.

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SetUnsharpMaskingFlag (  bool  _arg  )  [virtual]

template<class TInputImage, class TSparseOutputImage> virtual void itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >::SetUnsharpMaskingWeight (  NodeValueType  _arg  )  [virtual]

Use the image spacing information in calculations Use this option if you* want derivatives in physical space Default is UseImageSpacingOff* virtual void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::SetUseImageSpacing (  bool  _arg  )  [virtual, inherited]

virtual int itk::ImageSource< TSparseOutputImage >::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::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::ThreadedApplyUpdate (  TimeStepType  dt, const ThreadRegionType &  regionToProcess, int  threadId )  [protected, virtual, inherited]

virtual TimeStepType itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::ThreadedCalculateChange (  const ThreadRegionType &  regionToProcess, int  threadId )  [protected, virtual, inherited]

virtual void itk::ImageSource< TSparseOutputImage >::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()

virtual void itk::FiniteDifferenceSparseImageFilter< TInputImage , TSparseOutputImage >::ThreadedPrecalculateChange (  const ThreadRegionType &  regionToProcess, int  threadId )  [protected, virtual, inherited]

static ITK_THREAD_RETURN_TYPE itk::ImageSource< TSparseOutputImage >::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.

* endcode* In the above the two lines of code can be in* either order* * Note that it may be more efficient to* use a pipeline than to call itk::ImageSource< TSparseOutputImage >::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 from itk::ProcessObject.

* endcode* In the above the two lines of code can be in* either order* * Note that itk::ImageSource< TSparseOutputImage >::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 from itk::ProcessObject.

* endcode* * code* someFilter itk::ImageSource< TSparseOutputImage >::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 from itk::ProcessObject.

* image itk::ImageSource< TSparseOutputImage >::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 from itk::ProcessObject.

* anotherFilter itk::ImageSource< TSparseOutputImage >::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 from itk::ProcessObject.

Get the output data of this process object The output of this* function is not valid until an appropriate either explicitly or implicitly Both the filter* itself and the data object have itk::ImageSource< TSparseOutputImage >::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 from itk::ProcessObject.

Get the output data of this process object The output of this* function is not valid until an appropriate itk::ImageSource< TSparseOutputImage >::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 from itk::ProcessObject.

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 >, and itk::VTKImageImport< TOutputImage >.

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.

virtual void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::UseImageSpacingOff (   )  [virtual, inherited]

virtual void itk::FiniteDifferenceImageFilter< TInputImage , TSparseOutputImage >::UseImageSpacingOn (   )  [virtual, inherited]

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Member Data Documentation

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 unsigned lon itk::Object::AddObserver)(const EventObject &event, Command *) const [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 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 if an application has* images and they need to run a filter on then* run the filter on then run the filter on 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 itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::Again [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

This is a global flag that controls whether any itk::Object::debug [inherited]

Definition at line 94 of file itkObject.h.

* endcode* In the above itk::ImageSource< TSparseOutputImage >::example [inherited]

Definition at line 100 of file itkImageSource.h.

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 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 if an application has* images and they need to run a filter on then* run the filter on then run the filter on 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 this only makes sense for* filters that single type of input* * Other uses are also possible For a single input itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::filter [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

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 itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::filters [inherited]

Reimplemented from itk::ProcessObject. Definition at line 103 of file itkImageToImageFilter.h.

* * these methods end of hiding the versions from the superclass* ProcessObject whose arguments are DataObjects itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::Here [protected, inherited]

Definition at line 246 of file itkImageToImageFilter.h.

* itk::ImageSource< TSparseOutputImage >::image [inherited]

Definition at line 98 of file itkImageSource.h.

* endcode* * In this a someFilter and a anotherFilter are said* to constitute a b pipeline* * code* itk::ImageSource< TSparseOutputImage >::image [inherited]

Definition at line 92 of file itkImageSource.h.

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 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 if an application has* images and they need to run a filter on then* run the filter on then run the filter on* itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::images [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

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 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 if an application has* images and they need to run a filter on then* run the filter on itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::images [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

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 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 if an application has* images and they need to run a filter on itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::images [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

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 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 itk::ImageToImageFilter< TInputImage , TSparseOutputImage >::instance [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

TimeStamp itk::ProcessObject::m_OutputInformationMTime [protected, inherited]

Time when GenerateOutputInformation was last called. Definition at line 428 of file itkProcessObject.h.

int itk::LightObject::m_ReferenceCount [mutable, protected, inherited]

Number of uses of this object by other objects. Definition at line 119 of file itkLightObject.h.

SimpleFastMutexLock itk::LightObject::m_ReferenceCountLock [mutable, protected, inherited]

Mutex lock to protect modification to the reference count Definition at line 122 of file itkLightObject.h.

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

This flag indicates when the pipeline is executing. It prevents infinite recursion when pipelines have loops. Definition at line 425 of file itkProcessObject.h.

Get the output data of this process object The output of this* function is not valid until an appropriate either explicitly or implicitly Both the filter* itself and the data object have and both* methods update the data Here are three ways to use* a image is a pointer to some Image itk::ImageSource< TSparseOutputImage >::object [inherited]

Definition at line 79 of file itkImageSource.h.

Methods invoked by virtual 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 PrintSelf(std voi itk::LightObject::PrintHeader)(std::ostream &os, Indent indent) const [protected, inherited]

* endcode* In the above the two lines of code can be in* either order* * Note that it may be more efficient to* use a pipeline than to call the data generated is for the requested* itk::ImageSource< TSparseOutputImage >::Region [inherited]

Definition at line 110 of file itkImageSource.h.

* endcode* * In this itk::ImageSource< TSparseOutputImage >::situation [inherited]

Definition at line 88 of file itkImageSource.h.

Can the filter run in place To do itk::InPlaceImageFilter< TInputImage , TSparseOutputImage >::so [inherited]

Definition at line 99 of file itkInPlaceImageFilter.h.

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

• itkImplicitManifoldNormalVectorFilter.h

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