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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
*
* https://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 itkGradientNDAnisotropicDiffusionFunction_h
#define itkGradientNDAnisotropicDiffusionFunction_h
#include "itkScalarAnisotropicDiffusionFunction.h"
#include "itkNeighborhoodAlgorithm.h"
#include "itkNeighborhoodInnerProduct.h"
#include "itkDerivativeOperator.h"
namespace itk
{
/** \class GradientNDAnisotropicDiffusionFunction
*
* This class implements an N-dimensional version of the classic Perona-Malik
* anisotropic diffusion equation for scalar-valued images. See
* itkAnisotropicDiffusionFunction for an overview of the anisotropic diffusion
* framework and equation.
*
* \par
* The conductance term for this implementation is chosen as a function of the
* gradient magnitude of the image at each point, reducing the strength of
* diffusion at edge pixels.
*
* \f[C(\mathbf{x}) = e^{-(\frac{\parallel \nabla U(\mathbf{x}) \parallel}{K})^2}\f].
*
* \par
* The numerical implementation of this equation is similar to that described
* in the Perona-Malik paper below, but uses a more robust technique
* for gradient magnitude estimation and has been generalized to N-dimensions.
*
* \par References
* Pietro Perona and Jalhandra Malik, ``Scale-space and edge detection using
* anisotropic diffusion,'' IEEE Transactions on Pattern Analysis Machine
* Intelligence, vol. 12, pp. 629-639, 1990.
*
* \sa AnisotropicDiffusionFunction
* \sa VectorAnisotropicDiffusionFunction
* \sa VectorGradientAnisotropicDiffusionFunction
* \sa CurvatureNDAnisotropicDiffusionFunction
* \ingroup FiniteDifferenceFunctions
* \ingroup ImageEnhancement
* \ingroup ITKAnisotropicSmoothing
*/
template <typename TImage>
class ITK_TEMPLATE_EXPORT GradientNDAnisotropicDiffusionFunction : public ScalarAnisotropicDiffusionFunction<TImage>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(GradientNDAnisotropicDiffusionFunction);
/** Standard class type aliases. */
using Self = GradientNDAnisotropicDiffusionFunction;
using Superclass = ScalarAnisotropicDiffusionFunction<TImage>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(GradientNDAnisotropicDiffusionFunction);
/** Inherit some parameters from the superclass type. */
using typename Superclass::ImageType;
using typename Superclass::PixelType;
using typename Superclass::PixelRealType;
using typename Superclass::TimeStepType;
using typename Superclass::RadiusType;
using typename Superclass::NeighborhoodType;
using typename Superclass::FloatOffsetType;
using NeighborhoodSizeValueType = SizeValueType;
/** Inherit some parameters from the superclass type. */
static constexpr unsigned int ImageDimension = Superclass::ImageDimension;
/** Compute the equation value. */
PixelType
ComputeUpdate(const NeighborhoodType & it,
void * globalData,
const FloatOffsetType & offset = FloatOffsetType(0.0)) override;
/** This method is called prior to each iteration of the solver. */
void
InitializeIteration() override
{
m_K = static_cast<PixelType>(this->GetAverageGradientMagnitudeSquared() * this->GetConductanceParameter() *
this->GetConductanceParameter() * -2.0f);
}
protected:
GradientNDAnisotropicDiffusionFunction();
~GradientNDAnisotropicDiffusionFunction() override = default;
/** Inner product function. */
NeighborhoodInnerProduct<ImageType> m_InnerProduct{};
/** Slices for the ND neighborhood. */
std::slice x_slice[ImageDimension];
std::slice xa_slice[ImageDimension][ImageDimension];
std::slice xd_slice[ImageDimension][ImageDimension];
/** Derivative operator. */
DerivativeOperator<PixelType, Self::ImageDimension> m_DerivativeOperator{};
/** Modified global average gradient magnitude term. */
PixelType m_K{};
NeighborhoodSizeValueType m_Center{};
NeighborhoodSizeValueType m_Stride[ImageDimension]{};
static double m_MIN_NORM;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkGradientNDAnisotropicDiffusionFunction.hxx"
#endif
#endif
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