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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkGrayscaleConnectedClosingImageFilter.txx,v $
Language: C++
Date: $Date: 2006-12-15 21:40:37 $
Version: $Revision: 1.12 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkGrayscaleConnectedClosingImageFilter_txx
#define __itkGrayscaleConnectedClosingImageFilter_txx
#include "itkImageRegionIterator.h"
#include "itkImageRegionConstIterator.h"
#include "itkGrayscaleConnectedClosingImageFilter.h"
#include "itkReconstructionByErosionImageFilter.h"
#include "itkMinimumMaximumImageCalculator.h"
#include "itkProgressAccumulator.h"
namespace itk {
template <class TInputImage, class TOutputImage>
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>
::GrayscaleConnectedClosingImageFilter()
: m_NumberOfIterationsUsed( 1 )
{
m_Seed.Fill( NumericTraits<ITK_TYPENAME InputImageIndexType::OffsetValueType>::Zero );
m_FullyConnected = false;
}
template <class TInputImage, class TOutputImage>
void
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>
::GenerateInputRequestedRegion()
{
// call the superclass' implementation of this method
Superclass::GenerateInputRequestedRegion();
// We need all the input.
InputImagePointer input = const_cast<InputImageType *>(this->GetInput());
if( input )
{
input->SetRequestedRegion( input->GetLargestPossibleRegion() );
}
}
template <class TInputImage, class TOutputImage>
void
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>
::EnlargeOutputRequestedRegion(DataObject *)
{
this->GetOutput()
->SetRequestedRegion( this->GetOutput()->GetLargestPossibleRegion() );
}
template<class TInputImage, class TOutputImage>
void
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>
::GenerateData()
{
// Allocate the output
this->AllocateOutputs();
// construct a marker image to manipulate using reconstruction by
// dilation. the marker image will have the same pixel values as the
// input image at the seed pixel and will have a minimum everywhere
// else.
//
// compute the minimum pixel value in the input
typename MinimumMaximumImageCalculator<TInputImage>::Pointer calculator
= MinimumMaximumImageCalculator<TInputImage>::New();
calculator->SetImage( this->GetInput() );
calculator->ComputeMaximum();
InputImagePixelType maxValue;
maxValue = calculator->GetMaximum();
// compare this maximum value to the value at the seed pixel.
InputImagePixelType seedValue;
seedValue = this->GetInput()->GetPixel( m_Seed );
if (maxValue == seedValue)
{
itkWarningMacro(<< "GrayscaleConnectedClosingImageFilter: pixel value at seed point matches maximum value in image. Resulting image will have a constant value.");
this->GetOutput()->FillBuffer( maxValue );
this->UpdateProgress(1.0);
return;
}
// allocate a marker image
InputImagePointer markerPtr = InputImageType::New();
markerPtr->SetRegions( this->GetInput()->GetRequestedRegion() );
markerPtr->CopyInformation( this->GetInput() );
markerPtr->Allocate();
// fill the marker image with the maximum value from the input
markerPtr->FillBuffer( maxValue );
// mark the seed point
markerPtr->SetPixel( m_Seed, seedValue );
// Delegate to a geodesic dilation filter.
//
//
typename ReconstructionByErosionImageFilter<TInputImage, TInputImage>::Pointer
erode
= ReconstructionByErosionImageFilter<TInputImage, TInputImage>::New();
// Create a process accumulator for tracking the progress of this minipipeline
ProgressAccumulator::Pointer progress = ProgressAccumulator::New();
progress->SetMiniPipelineFilter(this);
progress->RegisterInternalFilter(erode,1.0f);
// set up the erode filter
//erode->RunOneIterationOff(); // run to convergence
erode->SetMarkerImage( markerPtr );
erode->SetMaskImage( this->GetInput() );
erode->SetFullyConnected( m_FullyConnected );
// graft our output to the erode filter to force the proper regions
// to be generated
erode->GraftOutput( this->GetOutput() );
// reconstruction by dilation
erode->Update();
// graft the output of the erode filter back onto this filter's
// output. this is needed to get the appropriate regions passed
// back.
this->GraftOutput( erode->GetOutput() );
}
template<class TInputImage, class TOutputImage>
void
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>
::PrintSelf(std::ostream &os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Seed point: " << m_Seed << std::endl;
os << indent << "Number of iterations used to produce current output: "
<< m_NumberOfIterationsUsed << std::endl;
os << indent << "FullyConnected: " << m_FullyConnected << std::endl;
}
}// end namespace itk
#endif
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