ITK
6.0.0
Insight 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://doi.org/10.54294/mrg5is
Definition at line 47 of file itkDiscreteGaussianDerivativeImageFunction.h.
Public Member Functions | |
OutputType | Evaluate (const PointType &point) const override |
OutputType | EvaluateAtContinuousIndex (const ContinuousIndexType &index) const override |
OutputType | EvaluateAtIndex (const IndexType &index) const override |
const char * | GetNameOfClass () const override |
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 | SetUseImageSpacing (bool _arg) |
virtual bool | GetUseImageSpacing () const |
virtual void | UseImageSpacingOn () |
virtual void | SetMaximumKernelWidth (unsigned int _arg) |
virtual unsigned int | GetMaximumKernelWidth () const |
virtual void | SetInterpolationMode (const InterpolationModeEnum _arg) |
virtual InterpolationModeEnum | GetInterpolationMode () const |
Public Member Functions inherited from itk::ImageFunction< TInputImage, double, double > | |
void | ConvertContinuousIndexToNearestIndex (const ContinuousIndexType &cindex, IndexType &index) const |
void | ConvertPointToContinuousIndex (const PointType &point, ContinuousIndexType &cindex) const |
OutputType | Evaluate (const PointType &point) const override=0 |
virtual double | EvaluateAtContinuousIndex (const ContinuousIndexType &index) const=0 |
virtual double | EvaluateAtIndex (const IndexType &index) const=0 |
virtual const ContinuousIndexType & | GetEndContinuousIndex () const |
virtual const IndexType & | GetEndIndex () const |
const InputImageType * | GetInputImage () const |
const char * | GetNameOfClass () const override |
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 |
void | ConvertPointToNearestIndex (const PointType &point, IndexType &index) const |
Public Member Functions inherited from itk::FunctionBase< Point< double, TInputImage::ImageDimension >, double > | |
virtual OutputType | Evaluate (const InputType &input) const=0 |
const char * | GetNameOfClass () const override |
Public Member Functions inherited from itk::Object | |
unsigned long | AddObserver (const EventObject &event, Command *cmd) const |
unsigned long | AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const |
LightObject::Pointer | CreateAnother () const override |
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 |
const char * | GetNameOfClass () const override |
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) const |
void | SetDebug (bool debugFlag) const |
void | SetReferenceCount (int) override |
void | UnRegister () const noexcept override |
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 | |
Pointer | Clone () const |
virtual Pointer | CreateAnother () const |
virtual void | Delete () |
virtual const char * | GetNameOfClass () const |
virtual int | GetReferenceCount () const |
void | Print (std::ostream &os, Indent indent=0) const |
virtual void | Register () const |
virtual void | SetReferenceCount (int) |
virtual void | UnRegister () const noexcept |
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 val) |
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, double, double > | |
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=default | |
Protected Member Functions inherited from itk::ImageFunction< TInputImage, double, double > | |
ImageFunction () | |
void | PrintSelf (std::ostream &os, Indent indent) const override |
~ImageFunction () override=default | |
Protected Member Functions inherited from itk::FunctionBase< Point< double, TInputImage::ImageDimension >, double > | |
FunctionBase ()=default | |
~FunctionBase () override=default | |
Protected Member Functions inherited from itk::Object | |
Object () | |
bool | PrintObservers (std::ostream &os, Indent indent) const |
void | PrintSelf (std::ostream &os, Indent indent) const override |
virtual void | SetTimeStamp (const TimeStamp &timeStamp) |
~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 | PrintSelf (std::ostream &os, Indent indent) const |
virtual void | PrintTrailer (std::ostream &os, Indent indent) const |
virtual | ~LightObject () |
Private Attributes | |
KernelType | m_DerivativeKernel {} |
InterpolationModeEnum | m_InterpolationMode { InterpolationModeEnum::NearestNeighbourInterpolation } |
double | m_MaximumError { 0.005 } |
unsigned int | m_MaximumKernelWidth { 30 } |
bool | m_NormalizeAcrossScale { true } |
GaussianDerivativeOperatorArrayType | m_OperatorArray {} |
OperatorImageFunctionPointer | m_OperatorImageFunction {} |
OrderArrayType | m_Order {} |
bool | m_UseImageSpacing { true } |
VarianceArrayType | m_Variance {} |
Additional Inherited Members | |
Protected Attributes inherited from itk::ImageFunction< TInputImage, double, double > | |
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 59 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 88 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorType = itk::GaussianDerivativeOperator<TOutput, Self::ImageDimension2> |
Definition at line 85 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::InterpolationModeEnum = GaussianDerivativeOperatorEnums::InterpolationMode |
Definition at line 98 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::KernelType = Neighborhood<TOutput, Self::ImageDimension2> |
Precomputed N-dimensional derivative kernel.
Definition at line 91 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OperatorImageFunctionPointer = typename OperatorImageFunctionType::Pointer |
Definition at line 96 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 95 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::OrderArrayType = FixedArray<unsigned int, Self::ImageDimension2> |
Definition at line 83 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Pointer = SmartPointer<Self> |
Smart pointer type alias support
Definition at line 58 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Self = DiscreteGaussianDerivativeImageFunction |
Standard "Self" type alias
Definition at line 52 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::Superclass = ImageFunction<TInputImage, TOutput, TOutput> |
Standard "Superclass" type alias
Definition at line 55 of file itkDiscreteGaussianDerivativeImageFunction.h.
using itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >::VarianceArrayType = FixedArray<double, Self::ImageDimension2> |
Arrays for native types.
Definition at line 82 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Definition at line 218 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Evaluate the function at specified point.
Implements itk::ImageFunction< TInputImage, double, double >.
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Evaluate the function at specified ContinuousIndex position.
Implements itk::ImageFunction< TInputImage, double, double >.
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Evaluate the function at specified Index position
Implements itk::ImageFunction< TInputImage, double, double >.
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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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Reimplemented from itk::Object.
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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 211 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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Definition at line 223 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.
Reimplemented from itk::ImageFunction< TInputImage, double, double >.
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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 166 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Convenience method for setting the variance through the standard deviation.
Definition at line 143 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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Convenience method for setting the variance for all dimensions.
Definition at line 132 of file itkDiscreteGaussianDerivativeImageFunction.h.
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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 flag for using image spacing when calculating derivatives.
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Dimension of the underlying image.
Definition at line 76 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 252 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Interpolation mode.
Definition at line 264 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 240 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 245 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Flag for scale-space normalization of derivatives.
Definition at line 258 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Array of derivative operators, one for each dimension.
Definition at line 248 of file itkDiscreteGaussianDerivativeImageFunction.h.
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OperatorImageFunction
Definition at line 255 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Order of the derivatives in each dimension.
Definition at line 236 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Flag to indicate whether to use image spacing
Definition at line 261 of file itkDiscreteGaussianDerivativeImageFunction.h.
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Desired variance of the discrete Gaussian function.
Definition at line 233 of file itkDiscreteGaussianDerivativeImageFunction.h.