itkGaussianDerivativeOperator.h

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/*=========================================================================
 *
 *  Copyright Insight Software Consortium
 *
 *  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 itkGaussianDerivativeOperator_h
#define itkGaussianDerivativeOperator_h

#include "itkGaussianOperator.h"
#include "itkDerivativeOperator.h"

#include <algorithm>

namespace itk
{
template< typename TPixel, unsigned int VDimension = 2,
          typename TAllocator = NeighborhoodAllocator< TPixel > >
class ITK_TEMPLATE_EXPORT GaussianDerivativeOperator :
  public NeighborhoodOperator< TPixel, VDimension, TAllocator >
{
public:

  using Self = GaussianDerivativeOperator;
  using Superclass = NeighborhoodOperator< TPixel, VDimension, TAllocator >;

  using GaussianOperatorType = GaussianOperator< TPixel, VDimension, TAllocator >;
  using DerivativeOperatorType = DerivativeOperator< TPixel, VDimension, TAllocator >;

  GaussianDerivativeOperator() = default;

  GaussianDerivativeOperator(const Self & other);

  Self & operator=(const Self & other);


  void SetNormalizeAcrossScale(bool flag) { m_NormalizeAcrossScale = flag; }
  bool GetNormalizeAcrossScale() const { return m_NormalizeAcrossScale; }
  itkBooleanMacro(NormalizeAcrossScale);

  void SetVariance(const double variance) { m_Variance = variance; }
  double GetVariance() const { return m_Variance; }

  void SetSpacing(const double spacing) { m_Spacing = spacing; }
  double GetSpacing() const { return m_Spacing; }

  void SetMaximumError(const double maxerror)
  {
    constexpr double Min = 0.00001;
    const double Max = 1.0 - Min;

    m_MaximumError = std::max( Min, std::min( Max, maxerror ) );
  }
  double GetMaximumError() { return m_MaximumError; }

  void SetMaximumKernelWidth(unsigned int n)
  {
    m_MaximumKernelWidth = n;
  }

  void SetOrder(const unsigned int order) { m_Order = order;}
  unsigned int GetOrder() const { return m_Order; }

  void PrintSelf(std::ostream & os, Indent i) const override;

protected:

  using CoefficientVector = typename Superclass::CoefficientVector;

  static double ModifiedBesselI0(double);

  static double ModifiedBesselI1(double);

  static double ModifiedBesselI(int, double);

  CoefficientVector GenerateCoefficients() override;

  void Fill(const CoefficientVector & coeff) override
  { this->FillCenteredDirectional(coeff); }

private:

  /* methods for generations of the coeeficients for a gaussian
   * operator of 0-order respecting the remaining parameters */
  CoefficientVector GenerateGaussianCoefficients() const;

  const char * GetNameOfClass() const override
  {
    return "itkGaussianDerivativeOperator";
  }

  bool m_NormalizeAcrossScale{true};

  double m_Variance{1.0};

  double m_MaximumError{0.005};

  unsigned int m_MaximumKernelWidth{30};

  unsigned int m_Order{1};

  double m_Spacing{1.0};
};
} // namespace itk

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGaussianDerivativeOperator.hxx"
#endif

#endif