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ITK
4.1.0
Insight Segmentation and Registration Toolkit
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ITK
4.1.0
Insight Segmentation and Registration Toolkit
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#include <itkDiscreteGradientMagnitudeGaussianImageFunction.h>
Inheritance diagram for itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >: Collaboration diagram for itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >: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: http://hdl.handle.net/1926/1290
Definition at line 47 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef SmartPointer< const Self > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ConstPointer |
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 60 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef Superclass::ContinuousIndexType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ContinuousIndexType |
ContinuousIndex Type.
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 73 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef FixedArray< GaussianDerivativeOperatorType, 2 *itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorArrayType |
Array to store gaussian derivative operators one for each dimension
Definition at line 93 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef itk::GaussianDerivativeOperator< TOutput, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GaussianDerivativeOperatorType |
Definition at line 89 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef Superclass::IndexType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::IndexType |
Index Type.
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 71 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef Superclass::IndexValueType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::IndexValueType |
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 72 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef Superclass::InputImageType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::InputImageType |
Image dependent types
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 66 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef Superclass::InputPixelType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::InputPixelType |
InputPixel typedef support
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 70 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef FixedArray< KernelType, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::KernelArrayType |
Array to store precomputed N-dimensional kernels for the gradient components
Definition at line 100 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef Neighborhood< TOutput, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::KernelType |
Precomputed N-dimensional derivative kernel
Definition at line 96 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef OperatorImageFunctionType::Pointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OperatorImageFunctionPointer |
Definition at line 105 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef NeighborhoodOperatorImageFunction< InputImageType, TOutput > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OperatorImageFunctionType |
Image function that performs convolution with the neighborhood operator
Definition at line 104 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef FixedArray< unsigned int, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OrderArrayType |
Arrays for native types
Definition at line 85 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef Superclass::OutputType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::OutputType |
Output type
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 81 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef SmartPointer< Self > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Pointer |
Smart pointer typedef support
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 59 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef Superclass::PointType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::PointType |
Point Type.
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 74 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef DiscreteGradientMagnitudeGaussianImageFunction itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Self |
Standard "Self" typedef
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 53 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef ImageFunction< TInputImage, TOutput, TOutput > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Superclass |
Standard "Superclass" typedef
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 56 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| typedef FixedArray< double, itkGetStaticConstMacro(ImageDimension2) > itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::VarianceArrayType |
Arrays for native types
Definition at line 84 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| enum itk::DiscreteGradientMagnitudeGaussianImageFunction::InterpolationModeType |
Interpolation modes
Definition at line 108 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::DiscreteGradientMagnitudeGaussianImageFunction | ( | ) | [protected] |
| itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::DiscreteGradientMagnitudeGaussianImageFunction | ( | const Self & | ) | [inline, protected] |
Definition at line 193 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::~DiscreteGradientMagnitudeGaussianImageFunction | ( | ) | [inline, protected] |
Definition at line 195 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| virtual::itk::LightObject::Pointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::CreateAnother | ( | void | ) | const [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.
| virtual OutputType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Evaluate | ( | const PointType & | point | ) | const [virtual] |
Evalutate the in the given dimension at specified point
| virtual OutputType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::EvaluateAtContinuousIndex | ( | const ContinuousIndexType & | index | ) | const [virtual] |
Evaluate the function at specified ContinousIndex position
| virtual OutputType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::EvaluateAtIndex | ( | const IndexType & | index | ) | const [virtual] |
Evaluate the function at specified Index position
| virtual InterpolationModeType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetInterpolationMode | ( | ) | const [virtual] |
Set/Get the interpolation mode.
| virtual double itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetMaximumError | ( | ) | const [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 unsigned int itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetMaximumKernelWidth | ( | ) | const [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 const char* itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetNameOfClass | ( | ) | const [virtual] |
Run-time type information (and related methods)
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
| virtual bool itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetNormalizeAcrossScale | ( | ) | const [virtual] |
Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
| virtual bool itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetUseImageSpacing | ( | ) | const [virtual] |
Set/Get the flag for using image spacing when calculating derivatives.
| virtual const VarianceArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::GetVariance | ( | ) | const [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 void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::Initialize | ( | void | ) | [inline, virtual] |
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 189 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| static Pointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::New | ( | ) | [static] |
Method for creation through the object factory
Reimplemented from itk::Object.
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::NormalizeAcrossScaleOff | ( | ) | [virtual] |
Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::NormalizeAcrossScaleOn | ( | ) | [virtual] |
Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
| void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::operator= | ( | const Self & | ) | [inline, protected] |
Mutex lock to protect modification to the reference count
Reimplemented from itk::ImageFunction< TInputImage, TOutput, TOutput >.
Definition at line 197 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::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::ImageFunction< TInputImage, TOutput, TOutput >.
| void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::RecomputeGaussianKernel | ( | ) | [protected] |
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetInputImage | ( | const InputImageType * | ptr | ) | [virtual] |
Set the input image.
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetInterpolationMode | ( | InterpolationModeType | _arg | ) | [virtual] |
Set/Get the interpolation mode.
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetMaximumError | ( | double | _arg | ) | [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 void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetMaximumKernelWidth | ( | unsigned int | _arg | ) | [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 void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetNormalizeAcrossScale | ( | bool | _arg | ) | [virtual] |
Set/Get the flag for calculating scale-space normalized derivatives. Normalized derivatives are obtained multiplying by the scale parameter t.
| void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetSigma | ( | const double | sigma | ) | [inline] |
Convenience method for setting the variance through the standard deviation
Definition at line 140 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetUseImageSpacing | ( | bool | _arg | ) | [virtual] |
Set/Get the flag for using image spacing when calculating derivatives.
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetVariance | ( | VarianceArrayType | _arg | ) | [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 void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetVariance | ( | double | data[] | ) | [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 void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::SetVariance | ( | double | variance | ) | [inline, virtual] |
Convenience method for setting the variance for all dimensions
Definition at line 131 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::UseImageSpacingOff | ( | ) | [virtual] |
Set/Get the flag for using image spacing when calculating derivatives.
| virtual void itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::UseImageSpacingOn | ( | ) | [virtual] |
Set/Get the flag for using image spacing when calculating derivatives.
const unsigned int itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::ImageDimension2 = InputImageType::ImageDimension [static] |
Dimension of the underlying image
Definition at line 78 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
InterpolationModeType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_InterpolationMode [private] |
Interpolation mode
Definition at line 236 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
KernelArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_KernelArray [private] |
Array of N-dimensional kernels used to calculate gradient components
Definition at line 224 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
double itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_MaximumError [private] |
Difference between the areas under the curves of the continuous and discrete Gaussian functions
Definition at line 211 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
unsigned int itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_MaximumKernelWidth [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 216 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
bool itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_NormalizeAcrossScale [private] |
Flag for scale-space normalization of derivatives
Definition at line 230 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
GaussianDerivativeOperatorArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_OperatorArray [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 221 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
OperatorImageFunctionPointer itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_OperatorImageFunction [private] |
OperatorImageFunction
Definition at line 227 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
bool itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_UseImageSpacing [private] |
Flag to indicate whether to use image spacing
Definition at line 233 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
VarianceArrayType itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >::m_Variance [private] |
Desired variance of the discrete Gaussian function
Definition at line 207 of file itkDiscreteGradientMagnitudeGaussianImageFunction.h.
1.7.6.1
