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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 itkLandweberDeconvolutionImageFilter_hxx
#define itkLandweberDeconvolutionImageFilter_hxx
namespace itk
{
template <typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision>
LandweberDeconvolutionImageFilter<TInputImage, TKernelImage, TOutputImage, TInternalPrecision>::
LandweberDeconvolutionImageFilter()
{
m_Alpha = 0.1;
m_TransformedInput = nullptr;
}
template <typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision>
LandweberDeconvolutionImageFilter<TInputImage, TKernelImage, TOutputImage, TInternalPrecision>::
~LandweberDeconvolutionImageFilter()
{
m_TransformedInput = nullptr;
}
template <typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision>
void
LandweberDeconvolutionImageFilter<TInputImage, TKernelImage, TOutputImage, TInternalPrecision>::Initialize(
ProgressAccumulator * progress,
float progressWeight,
float iterationProgressWeight)
{
this->Superclass::Initialize(progress, 0.5f * progressWeight, iterationProgressWeight);
this->PrepareInput(this->GetInput(), m_TransformedInput, progress, 0.5f * progressWeight);
// Set up minipipeline to compute estimate at each iteration
m_LandweberFilter = LandweberFilterType::New();
LandweberFunctor functor;
functor.m_Alpha = m_Alpha;
m_LandweberFilter->SetFunctor(functor);
m_LandweberFilter->SetNumberOfWorkUnits(this->GetNumberOfWorkUnits());
// Transform of current estimate will be set as input 1 in Iteration()
m_LandweberFilter->SetInput2(this->m_TransferFunction);
m_LandweberFilter->SetInput3(m_TransformedInput);
m_LandweberFilter->ReleaseDataFlagOn();
progress->RegisterInternalFilter(m_LandweberFilter, 0.3f * iterationProgressWeight);
m_IFFTFilter = IFFTFilterType::New();
m_IFFTFilter->SetNumberOfWorkUnits(this->GetNumberOfWorkUnits());
m_IFFTFilter->SetActualXDimensionIsOdd(this->GetXDimensionIsOdd());
m_IFFTFilter->SetInput(m_LandweberFilter->GetOutput());
m_IFFTFilter->ReleaseDataFlagOn();
progress->RegisterInternalFilter(m_IFFTFilter, 0.7f * iterationProgressWeight);
}
template <typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision>
void
LandweberDeconvolutionImageFilter<TInputImage, TKernelImage, TOutputImage, TInternalPrecision>::Iteration(
ProgressAccumulator * progress,
float iterationProgressWeight)
{
// Set up minipipeline to compute the new estimate
InternalComplexImagePointerType transformedEstimate;
this->TransformPaddedInput(this->m_CurrentEstimate, transformedEstimate, progress, 0.1f * iterationProgressWeight);
// Set the inputs
m_LandweberFilter->SetInput1(transformedEstimate);
// Trigger the update
m_IFFTFilter->UpdateLargestPossibleRegion();
// Store the current estimate
this->m_CurrentEstimate = m_IFFTFilter->GetOutput();
this->m_CurrentEstimate->DisconnectPipeline();
}
template <typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision>
void
LandweberDeconvolutionImageFilter<TInputImage, TKernelImage, TOutputImage, TInternalPrecision>::Finish(
ProgressAccumulator * progress,
float progressWeight)
{
this->Superclass::Finish(progress, progressWeight);
m_LandweberFilter = nullptr;
m_IFFTFilter = nullptr;
}
template <typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision>
void
LandweberDeconvolutionImageFilter<TInputImage, TKernelImage, TOutputImage, TInternalPrecision>::PrintSelf(
std::ostream & os,
Indent indent) const
{
this->Superclass::PrintSelf(os, indent);
os << indent << "Alpha: " << m_Alpha << std::endl;
}
} // end namespace itk
#endif
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