itkBSplineInterpolateImageFunction.h

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 *  Copyright NumFOCUS
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 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
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 *  distributed under the License is distributed on an "AS IS" BASIS,
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 *  See the License for the specific language governing permissions and
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/*=========================================================================
 *
 *  Portions of this file are subject to the VTK Toolkit Version 3 copyright.
 *
 *  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
 *
 *  For complete copyright, license and disclaimer of warranty information
 *  please refer to the NOTICE file at the top of the ITK source tree.
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#ifndef itkBSplineInterpolateImageFunction_h
#define itkBSplineInterpolateImageFunction_h
 
#include "itkInterpolateImageFunction.h"
#include "vnl/vnl_matrix.h"
 
#include "itkBSplineDecompositionImageFilter.h"
#include "itkConceptChecking.h"
#include "itkCovariantVector.h"
 
#include <memory> // For unique_ptr.
#include <vector>
 
namespace itk
{
template <typename TImageType, typename TCoordRep = double, typename TCoefficientType = double>
class ITK_TEMPLATE_EXPORT BSplineInterpolateImageFunction : public InterpolateImageFunction<TImageType, TCoordRep>
{
public:
  ITK_DISALLOW_COPY_AND_MOVE(BSplineInterpolateImageFunction);
 
  using Self = BSplineInterpolateImageFunction;
  using Superclass = InterpolateImageFunction<TImageType, TCoordRep>;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
 
  itkTypeMacro(BSplineInterpolateImageFunction, InterpolateImageFunction);
 
  itkNewMacro(Self);
 
  using typename Superclass::OutputType;
 
  using typename Superclass::InputImageType;
 
  static constexpr unsigned int ImageDimension = Superclass::ImageDimension;
 
  using typename Superclass::IndexType;
 
  using typename Superclass::SizeType;
 
  using typename Superclass::ContinuousIndexType;
 
  using typename Superclass::PointType;
 
  using Iterator = ImageLinearIteratorWithIndex<TImageType>;
 
  using CoefficientDataType = TCoefficientType;
  using CoefficientImageType = Image<CoefficientDataType, Self::ImageDimension>;
 
  using CoefficientFilter = BSplineDecompositionImageFilter<TImageType, CoefficientImageType>;
  using CoefficientFilterPointer = typename CoefficientFilter::Pointer;
 
  using CovariantVectorType = CovariantVector<OutputType, Self::ImageDimension>;
 
  OutputType
  Evaluate(const PointType & point) const override
  {
    const ContinuousIndexType index =
      this->GetInputImage()->template TransformPhysicalPointToContinuousIndex<TCoordRep>(point);
    // No thread info passed in, so call method that doesn't need thread ID.
    return (this->EvaluateAtContinuousIndex(index));
  }
  virtual OutputType
  Evaluate(const PointType & point, ThreadIdType threadId) const
  {
    const ContinuousIndexType index =
      this->GetInputImage()->template TransformPhysicalPointToContinuousIndex<TCoordRep>(point);
    return (this->EvaluateAtContinuousIndex(index, threadId));
  }
 
  OutputType
  EvaluateAtContinuousIndex(const ContinuousIndexType & index) const override
  {
    // Don't know thread information, make evaluateIndex, weights on the stack.
    // Slower, but safer.
    vnl_matrix<long>   evaluateIndex(ImageDimension, (m_SplineOrder + 1));
    vnl_matrix<double> weights(ImageDimension, (m_SplineOrder + 1));
 
    // Pass evaluateIndex, weights by reference. They're only good as long
    // as this method is in scope.
    return this->EvaluateAtContinuousIndexInternal(index, evaluateIndex, weights);
  }
 
  virtual OutputType
  EvaluateAtContinuousIndex(const ContinuousIndexType & x, ThreadIdType threadId) const
  {
    // Pass evaluateIndex, weights by reference. Different threadIDs get different instances.
    return this->EvaluateAtContinuousIndexInternal(x, m_ThreadedEvaluateIndex[threadId], m_ThreadedWeights[threadId]);
  }
 
  CovariantVectorType
  EvaluateDerivative(const PointType & point) const
  {
    const ContinuousIndexType index =
      this->GetInputImage()->template TransformPhysicalPointToContinuousIndex<TCoordRep>(point);
 
    // No thread info passed in, so call method that doesn't need thread ID.
    return (this->EvaluateDerivativeAtContinuousIndex(index));
  }
 
  CovariantVectorType
  EvaluateDerivative(const PointType & point, ThreadIdType threadId) const
  {
    const ContinuousIndexType index =
      this->GetInputImage()->template TransformPhysicalPointToContinuousIndex<TCoordRep>(point);
    return (this->EvaluateDerivativeAtContinuousIndex(index, threadId));
  }
 
  CovariantVectorType
  EvaluateDerivativeAtContinuousIndex(const ContinuousIndexType & x) const
  {
    // Don't know thread information, make evaluateIndex, weights,
    // weightsDerivative
    // on the stack.
    // Slower, but safer.
    vnl_matrix<long>   evaluateIndex(ImageDimension, (m_SplineOrder + 1));
    vnl_matrix<double> weights(ImageDimension, (m_SplineOrder + 1));
    vnl_matrix<double> weightsDerivative(ImageDimension, (m_SplineOrder + 1));
 
    // Pass evaluateIndex, weights, weightsDerivative by reference. They're only
    // good
    // as long as this method is in scope.
    return this->EvaluateDerivativeAtContinuousIndexInternal(x, evaluateIndex, weights, weightsDerivative);
  }
 
  CovariantVectorType
  EvaluateDerivativeAtContinuousIndex(const ContinuousIndexType & x, ThreadIdType threadId) const
  {
    return this->EvaluateDerivativeAtContinuousIndexInternal(
      x, m_ThreadedEvaluateIndex[threadId], m_ThreadedWeights[threadId], m_ThreadedWeightsDerivative[threadId]);
  }
 
  void
  EvaluateValueAndDerivative(const PointType & point, OutputType & value, CovariantVectorType & deriv) const
  {
    const ContinuousIndexType index =
      this->GetInputImage()->template TransformPhysicalPointToContinuousIndex<TCoordRep>(point);
 
    // No thread info passed in, so call method that doesn't need thread ID.
    this->EvaluateValueAndDerivativeAtContinuousIndex(index, value, deriv);
  }
 
  void
  EvaluateValueAndDerivative(const PointType &     point,
                             OutputType &          value,
                             CovariantVectorType & deriv,
                             ThreadIdType          threadId) const
  {
    const ContinuousIndexType index =
      this->GetInputImage()->template TransformPhysicalPointToContinuousIndex<TCoordRep>(point);
    this->EvaluateValueAndDerivativeAtContinuousIndex(index, value, deriv, threadId);
  }
 
  void
  EvaluateValueAndDerivativeAtContinuousIndex(const ContinuousIndexType & x,
                                              OutputType &                value,
                                              CovariantVectorType &       deriv) const
  {
    // Don't know thread information, make evaluateIndex, weights,
    // weightsDerivative
    // on the stack.
    // Slower, but safer.
    vnl_matrix<long>   evaluateIndex(ImageDimension, (m_SplineOrder + 1));
    vnl_matrix<double> weights(ImageDimension, (m_SplineOrder + 1));
    vnl_matrix<double> weightsDerivative(ImageDimension, (m_SplineOrder + 1));
 
    // Pass evaluateIndex, weights, weightsDerivative by reference. They're only
    // good
    // as long as this method is in scope.
    this->EvaluateValueAndDerivativeAtContinuousIndexInternal(
      x, value, deriv, evaluateIndex, weights, weightsDerivative);
  }
 
  void
  EvaluateValueAndDerivativeAtContinuousIndex(const ContinuousIndexType & x,
                                              OutputType &                value,
                                              CovariantVectorType &       derivativeValue,
                                              ThreadIdType                threadId) const
  {
    this->EvaluateValueAndDerivativeAtContinuousIndexInternal(x,
                                                              value,
                                                              derivativeValue,
                                                              m_ThreadedEvaluateIndex[threadId],
                                                              m_ThreadedWeights[threadId],
                                                              m_ThreadedWeightsDerivative[threadId]);
  }
 
  void
  SetSplineOrder(unsigned int SplineOrder);
 
  itkGetConstMacro(SplineOrder, unsigned int);
 
  void
  SetNumberOfWorkUnits(ThreadIdType numThreads);
 
  itkGetConstMacro(NumberOfWorkUnits, ThreadIdType);
 
  void
  SetInputImage(const TImageType * inputData) override;
 
  itkSetMacro(UseImageDirection, bool);
  itkGetConstMacro(UseImageDirection, bool);
  itkBooleanMacro(UseImageDirection);
  SizeType
  GetRadius() const override
  {
    return SizeType::Filled(m_SplineOrder + 1);
  }
 
protected:
  virtual OutputType
  EvaluateAtContinuousIndexInternal(const ContinuousIndexType & x,
                                    vnl_matrix<long> &          evaluateIndex,
                                    vnl_matrix<double> &        weights) const;
 
  virtual void
  EvaluateValueAndDerivativeAtContinuousIndexInternal(const ContinuousIndexType & x,
                                                      OutputType &                value,
                                                      CovariantVectorType &       derivativeValue,
                                                      vnl_matrix<long> &          evaluateIndex,
                                                      vnl_matrix<double> &        weights,
                                                      vnl_matrix<double> &        weightsDerivative) const;
 
  virtual CovariantVectorType
  EvaluateDerivativeAtContinuousIndexInternal(const ContinuousIndexType & x,
                                              vnl_matrix<long> &          evaluateIndex,
                                              vnl_matrix<double> &        weights,
                                              vnl_matrix<double> &        weightsDerivative) const;
 
  BSplineInterpolateImageFunction();
  ~BSplineInterpolateImageFunction() override = default;
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
 
  // These are needed by the smoothing spline routine.
  // temp storage for processing of Coefficients
  std::vector<CoefficientDataType> m_Scratch{};
  // Image size
  typename TImageType::SizeType m_DataLength{};
  // User specified spline order (3rd or cubic is the default)
  unsigned int m_SplineOrder{};
 
  // Spline coefficients
  typename CoefficientImageType::ConstPointer m_Coefficients{};
 
private:
  void
  SetInterpolationWeights(const ContinuousIndexType & x,
                          const vnl_matrix<long> &    EvaluateIndex,
                          vnl_matrix<double> &        weights,
                          unsigned int                splineOrder) const;
 
  void
  SetDerivativeWeights(const ContinuousIndexType & x,
                       const vnl_matrix<long> &    EvaluateIndex,
                       vnl_matrix<double> &        weights,
                       unsigned int                splineOrder) const;
 
  void
  GeneratePointsToIndex();
 
  void
  DetermineRegionOfSupport(vnl_matrix<long> &          evaluateIndex,
                           const ContinuousIndexType & x,
                           unsigned int                splineOrder) const;
 
  void
  ApplyMirrorBoundaryConditions(vnl_matrix<long> & evaluateIndex, unsigned int splineOrder) const;
 
  Iterator m_CIterator{};                         // Iterator for
                                                  // traversing spline
                                                  // coefficients.
  unsigned long m_MaxNumberInterpolationPoints{}; // number of
                                                  // neighborhood
                                                  // points used for
                                                  // interpolation
  std::vector<IndexType> m_PointsToIndex{};       // Preallocation of
                                                  // interpolation
                                                  // neighborhood
                                                  // indices
 
  CoefficientFilterPointer m_CoefficientFilter{};
 
  // flag to take or not the image direction into account when computing the
  // derivatives.
  bool m_UseImageDirection{};
 
  ThreadIdType                          m_NumberOfWorkUnits{};
  std::unique_ptr<vnl_matrix<long>[]>   m_ThreadedEvaluateIndex;
  std::unique_ptr<vnl_matrix<double>[]> m_ThreadedWeights;
  std::unique_ptr<vnl_matrix<double>[]> m_ThreadedWeightsDerivative;
};
} // namespace itk
 
#ifndef ITK_MANUAL_INSTANTIATION
#  include "itkBSplineInterpolateImageFunction.hxx"
#endif
 
#endif