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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 itkIterativeDeconvolutionImageFilter_hxx
#define itkIterativeDeconvolutionImageFilter_hxx
#include "itkCastImageFilter.h"
#include "itkIterativeDeconvolutionImageFilter.h"
namespace itk
{
template< typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision >
IterativeDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage, TInternalPrecision >
::IterativeDeconvolutionImageFilter()
{
m_NumberOfIterations = 1;
m_Iteration = 0;
m_StopIteration = false;
m_TransferFunction = ITK_NULLPTR;
m_CurrentEstimate = ITK_NULLPTR;
m_InputMTime = 0L;
m_KernelMTime = 0L;
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision >
IterativeDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage, TInternalPrecision >
::~IterativeDeconvolutionImageFilter()
{
m_TransferFunction = ITK_NULLPTR;
m_CurrentEstimate = ITK_NULLPTR;
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision >
void
IterativeDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage, TInternalPrecision >
::Initialize(ProgressAccumulator * progress, float progressWeight,
float itkNotUsed(iterationProgressWeight))
{
// Generate an estimate if there is none or if the input has changed.
if ( !this->m_CurrentEstimate ||
m_InputMTime != this->GetInput()->GetMTime() )
{
this->PadInput( this->GetInput(), m_CurrentEstimate, progress,
0.5f * progressWeight );
m_CurrentEstimate->DisconnectPipeline();
m_InputMTime = this->GetInput()->GetMTime();
}
// Generate the transfer function if there is none or if the kernel
// input has changed.
if ( !this->m_TransferFunction ||
m_KernelMTime != this->GetKernelImage()->GetMTime() )
{
this->PrepareKernel( this->GetKernelImage(), m_TransferFunction,
progress, 0.5f * progressWeight );
m_TransferFunction->DisconnectPipeline();
m_KernelMTime = this->GetKernelImage()->GetMTime();
}
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision >
void
IterativeDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage, TInternalPrecision >
::Finish(ProgressAccumulator * progress, float progressWeight)
{
this->CropOutput( m_CurrentEstimate, progress, progressWeight );
m_CurrentEstimate = ITK_NULLPTR;
m_TransferFunction = ITK_NULLPTR;
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision >
void
IterativeDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage, TInternalPrecision >
::GenerateInputRequestedRegion()
{
// Request the largest possible region for both input images.
if ( this->GetInput() )
{
typename InputImageType::Pointer imagePtr =
const_cast< InputImageType * >( this->GetInput() );
imagePtr->SetRequestedRegionToLargestPossibleRegion();
}
if ( this->GetKernelImage() )
{
// Input kernel is an image, cast away the constness so we can set
// the requested region.
typename KernelImageType::Pointer kernelPtr =
const_cast< KernelImageType * >( this->GetKernelImage() );
kernelPtr->SetRequestedRegionToLargestPossibleRegion();
}
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision >
void
IterativeDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage, TInternalPrecision >
::GenerateData()
{
// Create a process accumulator for tracking the progress of this minipipeline
ProgressAccumulator::Pointer progress = ProgressAccumulator::New();
progress->SetMiniPipelineFilter( this );
typename Superclass::InputImageConstPointer inputPtr = this->GetInput();
typename Superclass::OutputImagePointer outputPtr = this->GetOutput(0);
outputPtr->SetRequestedRegion( inputPtr->GetRequestedRegion() );
outputPtr->SetBufferedRegion( inputPtr->GetBufferedRegion() );
outputPtr->SetLargestPossibleRegion( inputPtr->GetLargestPossibleRegion() );
outputPtr->Allocate();
// Set up progress tracking
float iterationWeight = 0.8f / static_cast< float >( m_NumberOfIterations );
this->Initialize( progress, 0.1f, iterationWeight );
for ( m_Iteration = 0; m_Iteration < m_NumberOfIterations; ++m_Iteration )
{
this->InvokeEvent( IterationEvent() );
if ( m_StopIteration ) break;
this->Iteration( progress, iterationWeight );
}
this->Finish(progress, 0.1f);
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage, typename TInternalPrecision >
void
IterativeDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage, TInternalPrecision >
::PrintSelf(std::ostream & os, Indent indent) const
{
this->Superclass::PrintSelf( os, indent );
os << indent << "NumberOfIterations: " << m_NumberOfIterations << std::endl;
os << indent << "Iteration: " << m_Iteration << std::endl;
os << indent << "StopIteration: " << m_StopIteration << std::endl;
os << indent << "InputMTime: " << m_InputMTime << std::endl;
os << indent << "KernelMTime: " << m_KernelMTime << std::endl;
}
} // end namespace itk
#endif
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