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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 itkScalarAnisotropicDiffusionFunction_hxx
#define itkScalarAnisotropicDiffusionFunction_hxx
#include "itkConstNeighborhoodIterator.h"
#include "itkNeighborhoodInnerProduct.h"
#include "itkNeighborhoodAlgorithm.h"
#include "itkDerivativeOperator.h"
namespace itk
{
template <typename TImage>
void
ScalarAnisotropicDiffusionFunction<TImage>::CalculateAverageGradientMagnitudeSquared(TImage * ip)
{
using RNI_type = ConstNeighborhoodIterator<TImage>;
using SNI_type = ConstNeighborhoodIterator<TImage>;
using BFC_type = NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<TImage>;
using AccumulateType = typename NumericTraits<PixelType>::AccumulateType;
unsigned int i;
ZeroFluxNeumannBoundaryCondition<TImage> bc;
AccumulateType accumulator;
PixelRealType val;
SizeValueType counter;
BFC_type bfc;
typename RNI_type::RadiusType radius;
typename BFC_type::FaceListType::iterator fit;
RNI_type iterator_list[ImageDimension];
SNI_type face_iterator_list[ImageDimension];
DerivativeOperator<PixelType, ImageDimension> operator_list[ImageDimension];
SizeValueType Stride[ImageDimension];
SizeValueType Center[ImageDimension];
// Set up the derivative operators, one for each dimension
for (i = 0; i < ImageDimension; ++i)
{
operator_list[i].SetOrder(1);
operator_list[i].SetDirection(i);
operator_list[i].CreateDirectional();
radius[i] = operator_list[i].GetRadius()[i];
}
// Get the various region "faces" that are on the data set boundary.
typename BFC_type::FaceListType faceList = bfc(ip, ip->GetRequestedRegion(), radius);
fit = faceList.begin();
// Now do the actual processing
accumulator = AccumulateType{};
counter = SizeValueType{};
// First process the non-boundary region
// Instead of maintaining a single N-d neighborhood of pointers,
// we maintain a list of 1-d neighborhoods along each axial direction.
// This is more efficient for higher dimensions.
for (i = 0; i < ImageDimension; ++i)
{
iterator_list[i] = RNI_type(operator_list[i].GetRadius(), ip, *fit);
iterator_list[i].GoToBegin();
Center[i] = iterator_list[i].Size() / 2;
Stride[i] = iterator_list[i].GetStride(i);
}
while (!iterator_list[0].IsAtEnd())
{
++counter;
for (i = 0; i < ImageDimension; ++i)
{
val = iterator_list[i].GetPixel(Center[i] + Stride[i]) - iterator_list[i].GetPixel(Center[i] - Stride[i]);
PixelRealType tempval = val / -2.0f;
val = tempval * this->m_ScaleCoefficients[i];
accumulator += val * val;
++iterator_list[i];
}
}
// Go on to the next region(s). These are on the boundary faces.
++fit;
while (fit != faceList.end())
{
for (i = 0; i < ImageDimension; ++i)
{
face_iterator_list[i] = SNI_type(operator_list[i].GetRadius(), ip, *fit);
face_iterator_list[i].OverrideBoundaryCondition(&bc);
face_iterator_list[i].GoToBegin();
Center[i] = face_iterator_list[i].Size() / 2;
Stride[i] = face_iterator_list[i].GetStride(i);
}
while (!face_iterator_list[0].IsAtEnd())
{
++counter;
for (i = 0; i < ImageDimension; ++i)
{
val =
face_iterator_list[i].GetPixel(Center[i] + Stride[i]) - face_iterator_list[i].GetPixel(Center[i] - Stride[i]);
PixelRealType tempval = val / -2.0f;
val = tempval * this->m_ScaleCoefficients[i];
accumulator += val * val;
++face_iterator_list[i];
}
}
++fit;
}
this->SetAverageGradientMagnitudeSquared(static_cast<double>(accumulator / counter));
}
} // end namespace itk
#endif
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