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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 itkFFTDiscreteGaussianImageFilter_hxx
#define itkFFTDiscreteGaussianImageFilter_hxx
#include "itkGaussianOperator.h"
#include "itkGaussianImageSource.h"
#include "itkFFTConvolutionImageFilter.h"
#include "itkProgressAccumulator.h"
#include "itkImageAlgorithm.h"
#include "itkImageRegionIteratorWithIndex.h"
#include "itkMacro.h"
#include "itkVariableLengthVector.h"
namespace itk
{
template <typename TInputImage, typename TOutputImage>
void
FFTDiscreteGaussianImageFilter<TInputImage, TOutputImage>::GenerateInputRequestedRegion()
{
// call the superclass' implementation of this method. this should
// copy the output requested region to the input requested region
ImageToImageFilter<TInputImage, TOutputImage>::GenerateInputRequestedRegion();
// Get pointer to input
typename Superclass::InputImagePointer inputPtr = const_cast<TInputImage *>(this->GetInput());
if (inputPtr.IsNull())
{
return;
}
// get a copy of the input requested region (should equal the output
// requested region)
typename TInputImage::RegionType inputRequestedRegion;
inputRequestedRegion = inputPtr->GetRequestedRegion();
// pad the input requested region by the operator radius
RadiusType radius;
radius.Fill(0);
for (size_t dim = 0; dim < ImageDimension; ++dim)
{
radius[dim] = this->GetKernelRadius(dim);
}
inputRequestedRegion.PadByRadius(radius);
// crop the input requested region at the input's largest possible region
inputRequestedRegion.Crop(inputPtr->GetLargestPossibleRegion());
inputPtr->SetRequestedRegion(inputRequestedRegion);
}
template <typename TInputImage, typename TOutputImage>
void
FFTDiscreteGaussianImageFilter<TInputImage, TOutputImage>::SetInputBoundaryCondition(
const InputBoundaryConditionPointerType)
{
itkWarningMacro("FFTDiscreteGaussianImageFilter ignores InputBoundaryCondition, use RealBoundaryCondition instead");
}
template <typename TInputImage, typename TOutputImage>
auto
FFTDiscreteGaussianImageFilter<TInputImage, TOutputImage>::GenerateKernelImage() -> RealImageType *
{
m_KernelImage = RealImageType::New();
if (m_KernelSource == FFTDiscreteGaussianImageFilterEnums::KernelSource::OPERATORS)
{
// Get directional 1D Gaussian kernels to compose image
itk::VariableLengthVector<KernelType> directionalOperators;
directionalOperators.SetSize(this->GetFilterDimensionality());
RadiusType kernelSize;
kernelSize.Fill(1);
for (size_t dim = 0; dim < this->GetFilterDimensionality(); ++dim)
{
this->GenerateKernel(dim, directionalOperators[dim]);
kernelSize[dim] = directionalOperators[dim].GetRadius(dim) * 2 + 1;
}
// Set up kernel image
typename RealImageType::IndexType index;
index.Fill(0);
typename RealImageType::RegionType region;
region.SetSize(kernelSize);
region.SetIndex(index);
m_KernelImage->SetRegions(region);
m_KernelImage->Allocate();
m_KernelImage->CopyInformation(this->GetInput());
// Compute kernel image as product of vectors
itk::ImageRegionIteratorWithIndex<RealImageType> kernelIt(m_KernelImage, region);
while (!kernelIt.IsAtEnd())
{
auto imageIndex = kernelIt.GetIndex();
double val = 1;
for (size_t dim = 0; dim < directionalOperators.GetSize(); ++dim)
{
val *= directionalOperators[dim].GetElement(imageIndex[dim]);
}
kernelIt.Set(val);
++kernelIt;
}
}
else if (m_KernelSource == FFTDiscreteGaussianImageFilterEnums::KernelSource::IMAGE_SOURCE)
{
// Create kernel image for blurring in requested dimensions
using GaussianImageSourceType = GaussianImageSource<RealImageType>;
using KernelSizeType = typename GaussianImageSourceType::SizeType;
using KernelMeanType = typename GaussianImageSourceType::ArrayType;
typename GaussianImageSourceType::Pointer kernelSource = GaussianImageSourceType::New();
auto inputSpacing = this->GetInput()->GetSpacing();
auto inputOrigin = this->GetInput()->GetOrigin();
kernelSource->SetScale(1.0);
kernelSource->SetNormalized(true);
kernelSource->SetSpacing(inputSpacing);
kernelSource->SetOrigin(inputOrigin);
kernelSource->SetDirection(this->GetInput()->GetDirection());
KernelSizeType kernelSize;
kernelSize.Fill(1);
for (size_t dim = 0; dim < this->GetFilterDimensionality(); ++dim)
{
kernelSize[dim] = static_cast<SizeValueType>(this->GetKernelRadius(dim)) * 2 + 1;
}
kernelSource->SetSize(kernelSize);
KernelMeanType mean;
for (size_t dim = 0; dim < ImageDimension; ++dim)
{
double radius = (kernelSize[dim] - 1) / 2;
mean[dim] = inputSpacing[dim] * radius + inputOrigin[dim]; // center pixel pos
}
kernelSource->SetMean(mean);
kernelSource->SetSigma(this->GetSigmaArray());
kernelSource->Update();
m_KernelImage = kernelSource->GetOutput();
m_KernelImage->DisconnectPipeline();
}
else
{
itkExceptionMacro("Unknown kernel source enum");
}
return m_KernelImage.GetPointer();
}
template <typename TInputImage, typename TOutputImage>
void
FFTDiscreteGaussianImageFilter<TInputImage, TOutputImage>::GenerateData()
{
TOutputImage * output = this->GetOutput();
output->SetBufferedRegion(output->GetRequestedRegion());
output->Allocate();
// Create an internal image to protect the input image's metadata
// (e.g. RequestedRegion). The StreamingImageFilter changes the
// requested region as part of its normal processing.
auto localInput = TInputImage::New();
localInput->Graft(this->GetInput());
// Determine the dimensionality to filter
unsigned int filterDimensionality = this->GetFilterDimensionality();
if (filterDimensionality > ImageDimension)
{
filterDimensionality = ImageDimension;
}
if (filterDimensionality == 0)
{
// no smoothing, copy input to output
ImageAlgorithm::Copy(localInput.GetPointer(),
output,
this->GetOutput()->GetRequestedRegion(),
this->GetOutput()->GetRequestedRegion());
return;
}
// Create a process accumulator for tracking the progress of minipipeline
auto progress = ProgressAccumulator::New();
progress->SetMiniPipelineFilter(this);
RealImageType * kernelImage = GenerateKernelImage();
// Perform image convolution by FFT
m_ConvolutionImageFilter->SetInput(this->GetInput());
m_ConvolutionImageFilter->SetKernelImage(kernelImage);
m_ConvolutionImageFilter->SetBoundaryCondition(this->GetRealBoundaryCondition());
m_ConvolutionImageFilter->SetNormalize(false); // Kernel is already normalized
progress->RegisterInternalFilter(m_ConvolutionImageFilter, 1.0f);
// Graft this filters output onto the mini-pipeline so the mini-pipeline
// has the correct region ivars and will write to this filters bulk data
// output.
m_ConvolutionImageFilter->GraftOutput(output);
// Update the last filter in the mini-pipeline
m_ConvolutionImageFilter->Update();
// Graft the last output of the mini-pipeline onto this filters output so
// the final output has the correct region ivars and a handle to the final
// bulk data
this->GraftOutput(output);
}
} // namespace itk
#endif
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