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ITK
4.13.0
Insight Segmentation and Registration Toolkit
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#include <itkDiscreteHessianGaussianImageFunction.h>
Compute the Hessian Gaussian of an image at a specific location in space by calculating discrete second-order gaussian derivatives. This class is templated over the input image type.
The Initialize() method must be called after setting the parameters and before evaluating the function.
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/1290
Definition at line 46 of file itkDiscreteHessianGaussianImageFunction.h.
Public Member Functions | |
virtual ::itk::LightObject::Pointer | CreateAnother () const |
virtual OutputType | Evaluate (const PointType &point) const override |
virtual OutputType | EvaluateAtContinuousIndex (const ContinuousIndexType &index) const override |
virtual OutputType | EvaluateAtIndex (const IndexType &index) const override |
virtual const char * | GetNameOfClass () const |
virtual void | Initialize () |
virtual void | SetInputImage (const InputImageType *ptr) override |
void | SetSigma (const double sigma) |
virtual void | SetVariance (VarianceArrayType _arg) |
virtual const VarianceArrayType | GetVariance () const |
virtual void | SetVariance (double data[]) |
virtual void | SetVariance (double variance) |
virtual void | SetMaximumError (double _arg) |
virtual double | GetMaximumError () const |
virtual void | SetNormalizeAcrossScale (bool _arg) |
virtual bool | GetNormalizeAcrossScale () const |
virtual void | NormalizeAcrossScaleOn () |
virtual void | NormalizeAcrossScaleOff () |
virtual void | SetUseImageSpacing (bool _arg) |
virtual bool | GetUseImageSpacing () const |
virtual void | UseImageSpacingOn () |
virtual void | UseImageSpacingOff () |
virtual void | SetMaximumKernelWidth (unsigned int _arg) |
virtual unsigned int | GetMaximumKernelWidth () const |
virtual void | SetInterpolationMode (InterpolationModeType _arg) |
virtual InterpolationModeType | GetInterpolationMode () const |
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void | ConvertContinuousIndexToNearestIndex (const ContinuousIndexType &cindex, IndexType &index) const |
void | ConvertPointToContinuousIndex (const PointType &point, ContinuousIndexType &cindex) const |
void | ConvertPointToNearestIndex (const PointType &point, IndexType &index) const |
virtual SymmetricSecondRankTensor < TOutput, TInputImage::ImageDimension > | Evaluate (const PointType &point) const override=0 |
virtual SymmetricSecondRankTensor < TOutput, TInputImage::ImageDimension > | EvaluateAtContinuousIndex (const ContinuousIndexType &index) const =0 |
virtual SymmetricSecondRankTensor < TOutput, TInputImage::ImageDimension > | EvaluateAtIndex (const IndexType &index) const =0 |
virtual const ContinuousIndexType & | GetEndContinuousIndex () const |
virtual const IndexType & | GetEndIndex () const |
const InputImageType * | GetInputImage () const |
virtual const ContinuousIndexType & | GetStartContinuousIndex () const |
virtual const IndexType & | GetStartIndex () const |
virtual void | SetInputImage (const InputImageType *ptr) |
virtual bool | IsInsideBuffer (const IndexType &index) const |
virtual bool | IsInsideBuffer (const ContinuousIndexType &index) const |
virtual bool | IsInsideBuffer (const PointType &point) const |
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virtual OutputType | Evaluate (const InputType &input) const =0 |
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unsigned long | AddObserver (const EventObject &event, Command *) |
unsigned long | AddObserver (const EventObject &event, Command *) const |
virtual void | DebugOff () const |
virtual void | DebugOn () const |
Command * | GetCommand (unsigned long tag) |
bool | GetDebug () const |
MetaDataDictionary & | GetMetaDataDictionary () |
const MetaDataDictionary & | GetMetaDataDictionary () const |
virtual ModifiedTimeType | GetMTime () const |
virtual const TimeStamp & | GetTimeStamp () const |
bool | HasObserver (const EventObject &event) const |
void | InvokeEvent (const EventObject &) |
void | InvokeEvent (const EventObject &) const |
virtual void | Modified () const |
virtual void | Register () const override |
void | RemoveAllObservers () |
void | RemoveObserver (unsigned long tag) |
void | SetDebug (bool debugFlag) const |
void | SetMetaDataDictionary (const MetaDataDictionary &rhs) |
virtual void | SetReferenceCount (int) override |
virtual void | UnRegister () const noexceptoverride |
virtual void | SetObjectName (std::string _arg) |
virtual const std::string & | GetObjectName () const |
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virtual void | Delete () |
virtual int | GetReferenceCount () const |
itkCloneMacro (Self) | |
void | Print (std::ostream &os, Indent indent=0) const |
Static Public Member Functions | |
static Pointer | New () |
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static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool flag) |
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static void | BreakOnError () |
static Pointer | New () |
Static Public Attributes | |
static const unsigned int | ImageDimension2 = InputImageType::ImageDimension |
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static const unsigned int | ImageDimension |
Additional Inherited Members | |
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ContinuousIndexType | m_EndContinuousIndex |
IndexType | m_EndIndex |
InputImageConstPointer | m_Image |
ContinuousIndexType | m_StartContinuousIndex |
IndexType | m_StartIndex |
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AtomicInt< int > | m_ReferenceCount |
typedef SmartPointer< const Self > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::ConstPointer |
Definition at line 63 of file itkDiscreteHessianGaussianImageFunction.h.
typedef Superclass::ContinuousIndexType itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::ContinuousIndexType |
Definition at line 76 of file itkDiscreteHessianGaussianImageFunction.h.
typedef FixedArray< GaussianDerivativeOperatorType, 3 *itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorArrayType |
Array to store gaussian derivative operators from zero to second order (3*ImageDimension operators)
Definition at line 98 of file itkDiscreteHessianGaussianImageFunction.h.
typedef itk::GaussianDerivativeOperator< TOutput, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorType |
Definition at line 93 of file itkDiscreteHessianGaussianImageFunction.h.
typedef Superclass::IndexType itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::IndexType |
Definition at line 74 of file itkDiscreteHessianGaussianImageFunction.h.
typedef Superclass::IndexValueType itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::IndexValueType |
Definition at line 75 of file itkDiscreteHessianGaussianImageFunction.h.
typedef Superclass::InputImageType itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::InputImageType |
Image dependent types
Definition at line 69 of file itkDiscreteHessianGaussianImageFunction.h.
typedef Superclass::InputPixelType itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::InputPixelType |
Definition at line 73 of file itkDiscreteHessianGaussianImageFunction.h.
typedef FixedArray< KernelType, itkGetStaticConstMacro(ImageDimension2) * ( itkGetStaticConstMacro(ImageDimension2) + 1 ) / 2 > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::KernelArrayType |
Array to store precomputed N-dimensional kernels for the hessian components
Definition at line 105 of file itkDiscreteHessianGaussianImageFunction.h.
typedef Neighborhood< TOutput, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::KernelType |
Definition at line 100 of file itkDiscreteHessianGaussianImageFunction.h.
typedef OperatorImageFunctionType::Pointer itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::OperatorImageFunctionPointer |
Definition at line 111 of file itkDiscreteHessianGaussianImageFunction.h.
typedef NeighborhoodOperatorImageFunction< InputImageType, TOutput > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::OperatorImageFunctionType |
Image function that performs convolution with the neighborhood operator
Definition at line 110 of file itkDiscreteHessianGaussianImageFunction.h.
typedef Superclass::OutputType itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::OutputType |
Definition at line 87 of file itkDiscreteHessianGaussianImageFunction.h.
typedef SmartPointer< Self > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::Pointer |
Smart pointer typedef support
Definition at line 62 of file itkDiscreteHessianGaussianImageFunction.h.
typedef Superclass::PointType itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::PointType |
Definition at line 77 of file itkDiscreteHessianGaussianImageFunction.h.
typedef DiscreteHessianGaussianImageFunction itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::Self |
Standard "Self" typedef
Definition at line 54 of file itkDiscreteHessianGaussianImageFunction.h.
typedef ImageFunction< TInputImage, SymmetricSecondRankTensor< TOutput, TInputImage::ImageDimension >, TOutput > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::Superclass |
Standard "Superclass" typedef
Definition at line 59 of file itkDiscreteHessianGaussianImageFunction.h.
typedef SymmetricSecondRankTensor< TOutput, TInputImage::ImageDimension > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::TensorType |
Output type
Definition at line 86 of file itkDiscreteHessianGaussianImageFunction.h.
typedef FixedArray< double, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >::VarianceArrayType |
Definition at line 89 of file itkDiscreteHessianGaussianImageFunction.h.
enum itk::DiscreteHessianGaussianImageFunction::InterpolationModeType |
Interpolation modes
Enumerator | |
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NearestNeighbourInterpolation | |
LinearInterpolation |
Definition at line 114 of file itkDiscreteHessianGaussianImageFunction.h.
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inlineprotected |
Definition at line 201 of file itkDiscreteHessianGaussianImageFunction.h.
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inlineprotected |
Definition at line 203 of file itkDiscreteHessianGaussianImageFunction.h.
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Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.
Reimplemented from itk::Object.
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overridevirtual |
Evalutate the in the given dimension at specified point
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overridevirtual |
Evaluate the function at specified ContinuousIndex position
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overridevirtual |
Evaluate the function at specified Index position
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Set/Get the interpolation mode.
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Set/Get the desired maximum error of the gaussian approximation. Maximum error is the difference between the area under the discrete Gaussian curve and the area under the continuous Gaussian. Maximum error affects the Gaussian operator size. The value is clamped between 0.00001 and 0.99999.
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Set/Get a limit for growth of the kernel. Small maximum error values with large variances will yield very large kernel sizes. This value can be used to truncate a kernel in such instances. A warning will be given on truncation of the kernel.
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Run-time type information (and related methods)
Reimplemented from itk::ImageFunction< TInputImage, SymmetricSecondRankTensor< TOutput, TInputImage::ImageDimension >, TOutput >.
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Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
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Set/Get the flag for using image spacing when calculating derivatives.
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Set/Get the variance for the discrete Gaussian kernel. Sets the variance for individual dimensions. The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels.
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Initialize the Gaussian kernel. Call this method before evaluating the function. This method MUST be called after any changes to function parameters.
Definition at line 196 of file itkDiscreteHessianGaussianImageFunction.h.
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Method for creation through the object factory
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Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
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Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
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inlineprotected |
Definition at line 205 of file itkDiscreteHessianGaussianImageFunction.h.
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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::Object.
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overridevirtual |
Set the input image.
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Set/Get the interpolation mode.
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Set/Get the desired maximum error of the gaussian approximation. Maximum error is the difference between the area under the discrete Gaussian curve and the area under the continuous Gaussian. Maximum error affects the Gaussian operator size. The value is clamped between 0.00001 and 0.99999.
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Set/Get a limit for growth of the kernel. Small maximum error values with large variances will yield very large kernel sizes. This value can be used to truncate a kernel in such instances. A warning will be given on truncation of the kernel.
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Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
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Convenience method for setting the variance through the standard deviation
Definition at line 147 of file itkDiscreteHessianGaussianImageFunction.h.
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Set/Get the flag for using image spacing when calculating derivatives.
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Set/Get the variance for the discrete Gaussian kernel. Sets the variance for individual dimensions. The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels.
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Set/Get the variance for the discrete Gaussian kernel. Sets the variance for individual dimensions. The default is 0.0 in each dimension. If UseImageSpacing is true, the units are the physical units of your image. If UseImageSpacing is false then the units are pixels.
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Convenience method for setting the variance for all dimensions
Definition at line 138 of file itkDiscreteHessianGaussianImageFunction.h.
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Set/Get the flag for using image spacing when calculating derivatives.
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Set/Get the flag for using image spacing when calculating derivatives.
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Dimension of the underlying image
Definition at line 81 of file itkDiscreteHessianGaussianImageFunction.h.
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Interpolation mode
Definition at line 245 of file itkDiscreteHessianGaussianImageFunction.h.
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Array of N-dimensional kernels which are the result of convolving the operators for calculating hessian matrix derivatives
Definition at line 233 of file itkDiscreteHessianGaussianImageFunction.h.
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Difference between the areas under the curves of the continuous and discrete Gaussian functions
Definition at line 217 of file itkDiscreteHessianGaussianImageFunction.h.
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Maximum kernel size allowed. This value is used to truncate a kernel that has grown too large. A warning is given when the specified maximum error causes the kernel to exceed this size
Definition at line 222 of file itkDiscreteHessianGaussianImageFunction.h.
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Flag for scale-space normalization of derivatives
Definition at line 239 of file itkDiscreteHessianGaussianImageFunction.h.
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Array of derivative operators, one for each dimension and order. First N zero-order operators are stored, then N first-order and then N second-order making 3*N operators altogether where N=ImageDimension.
Definition at line 228 of file itkDiscreteHessianGaussianImageFunction.h.
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OperatorImageFunction
Definition at line 236 of file itkDiscreteHessianGaussianImageFunction.h.
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Flag to indicate whether to use image spacing
Definition at line 242 of file itkDiscreteHessianGaussianImageFunction.h.
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Desired variance of the discrete Gaussian function
Definition at line 213 of file itkDiscreteHessianGaussianImageFunction.h.