ITK
5.2.0
Insight Toolkit
|
#include <itkDiscreteGradientMagnitudeGaussianImageFunction.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 |
Public Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput > | |
TOutput | Evaluate (const PointType &point) const override=0 |
virtual TOutput | EvaluateAtContinuousIndex (const ContinuousIndexType &index) const=0 |
virtual TOutput | EvaluateAtIndex (const IndexType &index) const=0 |
const InputImageType * | GetInputImage () 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 |
void | ConvertPointToContinuousIndex (const PointType &point, ContinuousIndexType &cindex) const |
void | ConvertContinuousIndexToNearestIndex (const ContinuousIndexType &cindex, IndexType &index) const |
virtual const IndexType & | GetStartIndex () const |
virtual const IndexType & | GetEndIndex () const |
virtual const ContinuousIndexType & | GetStartContinuousIndex () const |
virtual const ContinuousIndexType & | GetEndContinuousIndex () const |
Public Member Functions inherited from itk::Object | |
unsigned long | AddObserver (const EventObject &event, Command *) |
unsigned long | AddObserver (const EventObject &event, Command *) const |
unsigned long | AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) 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 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 void | Delete () |
virtual int | GetReferenceCount () const |
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 val) |
Static Public Member Functions inherited from itk::LightObject | |
static void | BreakOnError () |
static Pointer | New () |
Additional Inherited Members | |
Protected Member Functions inherited from itk::ImageFunction< TInputImage, TOutput, TOutput > | |
ImageFunction () | |
~ImageFunction () override=default | |
void | PrintSelf (std::ostream &os, Indent indent) const override |
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 () | |
~Object () override | |
bool | PrintObservers (std::ostream &os, Indent indent) const |
virtual void | SetTimeStamp (const TimeStamp &timeStamp) |
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 () |
Protected Attributes inherited from itk::ImageFunction< TInputImage, TOutput, TOutput > | |
InputImageConstPointer | m_Image |
IndexType | m_StartIndex |
IndexType | m_EndIndex |
ContinuousIndexType | m_StartContinuousIndex |
ContinuousIndexType | m_EndContinuousIndex |
Protected Attributes inherited from itk::LightObject | |
std::atomic< int > | m_ReferenceCount |
Compute the discrete gradient magnitude gaussian 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 itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ConstPointer = SmartPointer<const Self> |
Definition at line 60 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ContinuousIndexType = typename Superclass::ContinuousIndexType |
Definition at line 73 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorArrayType = FixedArray<GaussianDerivativeOperatorType, 2 * Self::ImageDimension2> |
Array to store gaussian derivative operators one for each dimension
Definition at line 89 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorType = itk::GaussianDerivativeOperator<TOutput, Self::ImageDimension2> |
Definition at line 86 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::IndexType = typename Superclass::IndexType |
Definition at line 71 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::IndexValueType = typename Superclass::IndexValueType |
Definition at line 72 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::InputImageType = typename Superclass::InputImageType |
Image dependent types
Definition at line 69 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::InputPixelType = typename Superclass::InputPixelType |
Definition at line 70 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::InterpolationModeEnum = itk::GaussianDerivativeOperatorEnums::InterpolationMode |
Definition at line 102 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::KernelArrayType = FixedArray<KernelType, Self::ImageDimension2> |
Array to store precomputed N-dimensional kernels for the gradient components
Definition at line 96 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::KernelType = Neighborhood<TOutput, Self::ImageDimension2> |
Precomputed N-dimensional derivative kernel
Definition at line 92 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OperatorImageFunctionPointer = typename OperatorImageFunctionType::Pointer |
Definition at line 100 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OperatorImageFunctionType = NeighborhoodOperatorImageFunction<InputImageType, TOutput> |
Image function that performs convolution with the neighborhood operator
Definition at line 99 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OrderArrayType = FixedArray<unsigned int, Self::ImageDimension2> |
Definition at line 84 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OutputType = typename Superclass::OutputType |
Output type
Definition at line 80 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Pointer = SmartPointer<Self> |
Smart pointer type alias support
Definition at line 59 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::PointType = typename Superclass::PointType |
Definition at line 74 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Self = DiscreteGradientMagnitudeGaussianImageFunction |
Standard "Self" type alias
Definition at line 53 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Superclass = ImageFunction<TInputImage, TOutput, TOutput> |
Standard "Superclass" type alias
Definition at line 56 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
using itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::VarianceArrayType = FixedArray<double, Self::ImageDimension2> |
Arrays for native types
Definition at line 83 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
protected |
Desired variance of the discrete Gaussian function
|
inlineprotected |
Desired variance of the discrete Gaussian function
Definition at line 202 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
overrideprotecteddefault |
Desired variance of the discrete Gaussian function
|
virtual |
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.
|
override |
Evaluate the function in the given dimension at specified point
|
override |
Evaluate the function at specified ContinuousIndex position
|
override |
Evaluate the function at specified Index position
|
virtual |
Desired variance of the discrete Gaussian function
|
virtual |
Desired variance of the discrete Gaussian function
|
virtual |
Desired variance of the discrete Gaussian function
|
virtual |
Run-time type information (and related methods)
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
|
virtual |
Desired variance of the discrete Gaussian function
|
virtual |
Desired variance of the discrete Gaussian function
|
virtual |
Desired variance of the discrete Gaussian function
|
inlinevirtual |
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 195 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
static |
Method for creation through the object factory
|
virtual |
Desired variance of the discrete Gaussian function
|
virtual |
Desired variance of the discrete Gaussian function
|
inlineprotected |
Desired variance of the discrete Gaussian function
Definition at line 207 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
overrideprotectedvirtual |
Desired variance of the discrete Gaussian function
Reimplemented from itk::Object.
|
protected |
Desired variance of the discrete Gaussian function
|
override |
Set the input image.
|
virtual |
Set/Get the interpolation mode.
|
virtual |
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.
|
virtual |
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.
|
virtual |
Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
|
inline |
Convenience method for setting the variance through the standard deviation
Definition at line 144 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
virtual |
Set/Get the flag for using image spacing when calculating derivatives.
|
virtual |
Desired variance of the discrete Gaussian function
|
inlinevirtual |
Convenience method for setting the variance for all dimensions
Definition at line 134 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
virtual |
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
|
virtual |
Desired variance of the discrete Gaussian function
|
virtual |
Desired variance of the discrete Gaussian function
|
staticconstexpr |
Dimension of the underlying image
Definition at line 77 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
Interpolation mode
Definition at line 249 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
Array of N-dimensional kernels used to calculate gradient components
Definition at line 237 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
Difference between the areas under the curves of the continuous and discrete Gaussian functions
Definition at line 224 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
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 229 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
Flag for scale-space normalization of derivatives
Definition at line 243 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
Array of derivative operators, one for each dimension and order. First N zero-rder operators are stored, then N first-order making 2*N operators altogether where N=ImageDimension
Definition at line 234 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
OperatorImageFunction
Definition at line 240 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
Flag to indicate whether to use image spacing
Definition at line 246 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
|
private |
Desired variance of the discrete Gaussian function
Definition at line 220 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.