ITK
5.0.0
Insight Segmentation and Registration Toolkit
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#include <itkDiscreteGaussianDerivativeImageFunction.h>
Compute the discrete gaussian derivatives of an the image at a specific location in space, i.e. point, index or continuous index. This class computes a single derivative given the order in each direction (by default zero). 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 47 of file itkDiscreteGaussianDerivativeImageFunction.h.
Public Member Functions | |
virtual ::itk::LightObject::Pointer | CreateAnother () const |
OutputType | Evaluate (const PointType &point) const override |
OutputType | EvaluateAtContinuousIndex (const ContinuousIndexType &index) const override |
OutputType | EvaluateAtIndex (const IndexType &index) const override |
virtual const char * | GetNameOfClass () const |
virtual void | Initialize () |
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 | SetOrder (OrderArrayType _arg) |
virtual const OrderArrayType | GetOrder () const |
virtual void | SetOrder (unsigned int data[]) |
virtual void | SetOrder (unsigned int order) |
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 |
Public Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput > | |
void | ConvertContinuousIndexToNearestIndex (const ContinuousIndexType &cindex, IndexType &index) const |
void | ConvertPointToContinuousIndex (const PointType &point, ContinuousIndexType &cindex) const |
void | ConvertPointToNearestIndex (const PointType &point, IndexType &index) const |
TOutput | Evaluate (const PointType &point) const override=0 |
virtual TOutput | EvaluateAtContinuousIndex (const ContinuousIndexType &index) const =0 |
virtual TOutput | 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 |
Public Member Functions inherited from itk::Object | |
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 |
void | Register () const override |
void | RemoveAllObservers () |
void | RemoveObserver (unsigned long tag) |
void | SetDebug (bool debugFlag) const |
void | SetReferenceCount (int) override |
void | UnRegister () const noexceptoverride |
void | SetMetaDataDictionary (const MetaDataDictionary &rhs) |
void | SetMetaDataDictionary (MetaDataDictionary &&rrhs) |
virtual void | SetObjectName (std::string _arg) |
virtual const std::string & | GetObjectName () const |
Public Member Functions inherited from itk::LightObject | |
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 () |
Static Public Member Functions inherited from itk::Object | |
static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool flag) |
Static Public Member Functions inherited from itk::LightObject | |
static void | BreakOnError () |
static Pointer | New () |
Static Public Attributes | |
static constexpr unsigned int | ImageDimension2 = InputImageType::ImageDimension |
Static Public Attributes inherited from itk::ImageFunction< TInputImage, TOutput, TOutput > | |
static constexpr unsigned int | ImageDimension |
Protected Member Functions | |
DiscreteGaussianDerivativeImageFunction () | |
DiscreteGaussianDerivativeImageFunction (const Self &) | |
void | operator= (const Self &) |
void | PrintSelf (std::ostream &os, Indent indent) const override |
void | RecomputeGaussianKernel () |
~DiscreteGaussianDerivativeImageFunction () override | |
Protected Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput > | |
ImageFunction () | |
void | PrintSelf (std::ostream &os, Indent indent) const override |
~ImageFunction () override=default | |
Protected Member Functions inherited from itk::FunctionBase< Point< TOutput, TInputImage::ImageDimension >, TOutput > | |
FunctionBase ()=default | |
~FunctionBase () override=default | |
Protected Member Functions inherited from itk::Object | |
Object () | |
bool | PrintObservers (std::ostream &os, Indent indent) const |
virtual void | SetTimeStamp (const TimeStamp &time) |
~Object () override | |
Protected Member Functions inherited from itk::LightObject | |
virtual LightObject::Pointer | InternalClone () const |
LightObject () | |
virtual void | PrintHeader (std::ostream &os, Indent indent) const |
virtual void | PrintTrailer (std::ostream &os, Indent indent) const |
virtual | ~LightObject () |
Additional Inherited Members | |
Protected Attributes inherited from itk::ImageFunction< TInputImage, TOutput, TOutput > | |
ContinuousIndexType | m_EndContinuousIndex |
IndexType | m_EndIndex |
InputImageConstPointer | m_Image |
ContinuousIndexType | m_StartContinuousIndex |
IndexType | m_StartIndex |
Protected Attributes inherited from itk::LightObject | |
std::atomic< int > | m_ReferenceCount |
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::ConstPointer = SmartPointer< const Self > |
Definition at line 60 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::ContinuousIndexType = typename Superclass::ContinuousIndexType |
Definition at line 73 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorArrayType = FixedArray< GaussianDerivativeOperatorType, Self::ImageDimension2 > |
Array to store gaussian derivative operators one for each dimension.
Definition at line 91 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorType = itk::GaussianDerivativeOperator< TOutput, Self::ImageDimension2 > |
Definition at line 87 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::IndexType = typename Superclass::IndexType |
Definition at line 71 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::IndexValueType = typename Superclass::IndexValueType |
Definition at line 72 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::InputImageType = typename Superclass::InputImageType |
Image dependent types.
Definition at line 69 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::InputPixelType = typename Superclass::InputPixelType |
Definition at line 70 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::KernelType = Neighborhood< TOutput, Self::ImageDimension2 > |
Precomputed N-dimensional derivative kernel.
Definition at line 94 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OperatorImageFunctionPointer = typename OperatorImageFunctionType::Pointer |
Definition at line 100 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OperatorImageFunctionType = NeighborhoodOperatorImageFunction < InputImageType, TOutput > |
Image function that performs convolution with the neighborhood operator.
Definition at line 99 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OrderArrayType = FixedArray< unsigned int, Self::ImageDimension2 > |
Definition at line 84 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OutputType = typename Superclass::OutputType |
Output type.
Definition at line 80 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Pointer = SmartPointer< Self > |
Smart pointer type alias support
Definition at line 59 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::PointType = typename Superclass::PointType |
Definition at line 74 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Self = DiscreteGaussianDerivativeImageFunction |
Standard "Self" type alias
Definition at line 53 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Superclass = ImageFunction< TInputImage, TOutput, TOutput > |
Standard "Superclass" type alias
Definition at line 56 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::VarianceArrayType = FixedArray< double, Self::ImageDimension2 > |
Arrays for native types.
Definition at line 83 of file itkDiscreteGaussianDerivativeImageFunction.h.
enum itk::DiscreteGaussianDerivativeImageFunction::InterpolationModeType |
Interpolation modes.
Enumerator | |
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NearestNeighbourInterpolation | |
LinearInterpolation |
Definition at line 103 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Definition at line 209 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Definition at line 211 of file itkDiscreteGaussianDerivativeImageFunction.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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Evaluate the function at specified point.
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Evaluate the function at specified ContinuousIndex position.
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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, TOutput, 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 derivative order for an individual dimension.
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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 204 of file itkDiscreteGaussianDerivativeImageFunction.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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Definition at line 213 of file itkDiscreteGaussianDerivativeImageFunction.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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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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Set/Get the derivative order for an individual dimension.
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Set/Get the derivative order for an individual dimension.
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Convenience method for setting the order for all dimensions.
Definition at line 161 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Convenience method for setting the variance through the standard deviation.
Definition at line 139 of file itkDiscreteGaussianDerivativeImageFunction.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 129 of file itkDiscreteGaussianDerivativeImageFunction.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 77 of file itkDiscreteGaussianDerivativeImageFunction.h.
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N-dimensional kernel which is the result of convolving the operators for calculating derivatives.
Definition at line 240 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Interpolation mode.
Definition at line 252 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Difference between the areas under the curves of the continuous and discrete Gaussian functions.
Definition at line 228 of file itkDiscreteGaussianDerivativeImageFunction.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 233 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Flag for scale-space normalization of derivatives.
Definition at line 246 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Array of derivative operators, one for each dimension.
Definition at line 236 of file itkDiscreteGaussianDerivativeImageFunction.h.
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OperatorImageFunction
Definition at line 243 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Order of the derivatives in each dimension.
Definition at line 224 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Flag to indicate whether to use image spacing
Definition at line 249 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Desired variance of the discrete Gaussian function.
Definition at line 221 of file itkDiscreteGaussianDerivativeImageFunction.h.