itkDiscreteHessianGaussianImageFunction.h

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/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         http://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
 *
 *=========================================================================*/
#ifndef itkDiscreteHessianGaussianImageFunction_h
#define itkDiscreteHessianGaussianImageFunction_h
 
#include "itkNeighborhoodOperatorImageFunction.h"
#include "itkGaussianDerivativeOperator.h"
#include "itkSymmetricSecondRankTensor.h"
 
namespace itk
{
template <typename TInputImage, typename TOutput = double>
class ITK_TEMPLATE_EXPORT DiscreteHessianGaussianImageFunction
  : public ImageFunction<TInputImage, SymmetricSecondRankTensor<TOutput, TInputImage::ImageDimension>, TOutput>
{
public:
 
  using Self = DiscreteHessianGaussianImageFunction;
 
  using Superclass =
    ImageFunction<TInputImage, SymmetricSecondRankTensor<TOutput, TInputImage::ImageDimension>, TOutput>;
 
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
 
  itkNewMacro(Self);
 
  itkTypeMacro(DiscreteHessianGaussianImageFunction, ImageFunction);
 
  using InputImageType = typename Superclass::InputImageType;
  using InputPixelType = typename Superclass::InputPixelType;
  using IndexType = typename Superclass::IndexType;
  using IndexValueType = typename Superclass::IndexValueType;
  using ContinuousIndexType = typename Superclass::ContinuousIndexType;
  using PointType = typename Superclass::PointType;
 
  static constexpr unsigned int ImageDimension2 = InputImageType::ImageDimension;
 
  using TensorType = SymmetricSecondRankTensor<TOutput, TInputImage::ImageDimension>;
  using OutputType = typename Superclass::OutputType;
 
  using VarianceArrayType = FixedArray<double, Self::ImageDimension2>;
 
  using GaussianDerivativeOperatorType = itk::GaussianDerivativeOperator<TOutput, Self::ImageDimension2>;
 
  using GaussianDerivativeOperatorArrayType = FixedArray<GaussianDerivativeOperatorType, 3 * Self::ImageDimension2>;
 
  using KernelType = Neighborhood<TOutput, Self::ImageDimension2>;
 
  using KernelArrayType = FixedArray<KernelType, Self::ImageDimension2 *(Self::ImageDimension2 + 1) / 2>;
 
  using OperatorImageFunctionType = NeighborhoodOperatorImageFunction<InputImageType, TOutput>;
  using OperatorImageFunctionPointer = typename OperatorImageFunctionType::Pointer;
 
  using InterpolationModeEnum = itk::GaussianDerivativeOperatorEnums::InterpolationMode;
#if !defined(ITK_LEGACY_REMOVE)
 
  static constexpr InterpolationModeEnum NearestNeighbourInterpolation =
    InterpolationModeEnum::NearestNeighbourInterpolation;
  static constexpr InterpolationModeEnum LinearInterpolation = InterpolationModeEnum::LinearInterpolation;
#endif
 
public:
  OutputType
  Evaluate(const PointType & point) const override;
 
  OutputType
  EvaluateAtIndex(const IndexType & index) const override;
 
  OutputType
  EvaluateAtContinuousIndex(const ContinuousIndexType & index) const override;
 
  itkSetMacro(Variance, VarianceArrayType);
  itkGetConstMacro(Variance, const VarianceArrayType);
  itkSetVectorMacro(Variance, double, VarianceArrayType::Length);
 
  virtual void
  SetVariance(double variance)
  {
    m_Variance.Fill(variance);
    this->Modified();
  }
 
  void
  SetSigma(const double sigma)
  {
    SetVariance(sigma * sigma);
  }
 
  itkSetClampMacro(MaximumError, double, 0.00001, 0.99999);
  itkGetConstMacro(MaximumError, double);
 
  itkSetMacro(NormalizeAcrossScale, bool);
  itkGetConstMacro(NormalizeAcrossScale, bool);
  itkBooleanMacro(NormalizeAcrossScale);
 
  itkSetMacro(UseImageSpacing, bool);
  itkGetConstMacro(UseImageSpacing, bool);
  itkBooleanMacro(UseImageSpacing);
 
  itkSetMacro(MaximumKernelWidth, unsigned int);
  itkGetConstMacro(MaximumKernelWidth, unsigned int);
 
  itkSetEnumMacro(InterpolationMode, InterpolationModeEnum);
  itkGetEnumMacro(InterpolationMode, InterpolationModeEnum);
 
  void
  SetInputImage(const InputImageType * ptr) override;
 
  virtual void
  Initialize()
  {
    RecomputeGaussianKernel();
  }
 
protected:
  DiscreteHessianGaussianImageFunction();
  DiscreteHessianGaussianImageFunction(const Self &) {}
 
  ~DiscreteHessianGaussianImageFunction() override = default;
 
  void
  operator=(const Self &)
  {}
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
 
  void
  RecomputeGaussianKernel();
 
private:
  VarianceArrayType m_Variance;
 
  double m_MaximumError{ 0.005 };
 
  unsigned int m_MaximumKernelWidth{ 30 };
 
  mutable GaussianDerivativeOperatorArrayType m_OperatorArray;
 
  KernelArrayType m_KernelArray;
 
  OperatorImageFunctionPointer m_OperatorImageFunction;
 
  bool m_NormalizeAcrossScale{ true };
 
  bool m_UseImageSpacing{ true };
 
  InterpolationModeEnum m_InterpolationMode{ InterpolationModeEnum::NearestNeighbourInterpolation };
};
} // namespace itk
 
#ifndef ITK_MANUAL_INSTANTIATION
#  include "itkDiscreteHessianGaussianImageFunction.hxx"
#endif
 
#endif