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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkDirectedHausdorffDistanceImageFilter.txx,v $
Language: C++
Date: $Date: 2008-01-19 19:50:01 $
Version: $Revision: 1.10 $
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 _itkDirectedHausdorffDistanceImageFilter_txx
#define _itkDirectedHausdorffDistanceImageFilter_txx
#include "itkDirectedHausdorffDistanceImageFilter.h"
#include "itkImageRegionIterator.h"
#include "itkImageRegionConstIterator.h"
#include "itkNumericTraits.h"
#include "itkDanielssonDistanceMapImageFilter.h"
#include "itkProgressReporter.h"
namespace itk {
template<class TInputImage1, class TInputImage2>
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::DirectedHausdorffDistanceImageFilter(): m_MaxDistance(1)
{
// this filter requires two input images
this->SetNumberOfRequiredInputs( 2 );
m_DistanceMap = NULL;
m_DirectedHausdorffDistance = NumericTraits<RealType>::Zero;
}
template<class TInputImage1, class TInputImage2>
void
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::SetInput2( const TInputImage2 * image )
{
this->SetNthInput(1, const_cast<TInputImage2 *>( image ) );
}
template<class TInputImage1, class TInputImage2>
const typename DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::InputImage2Type *
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::GetInput2()
{
return static_cast< const TInputImage2 * >
(this->ProcessObject::GetInput(1));
}
template<class TInputImage1, class TInputImage2>
void
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::GenerateInputRequestedRegion()
{
Superclass::GenerateInputRequestedRegion();
// this filter requires:
// - the largeset possible region of the first image
// - the corresponding region of the second image
if ( this->GetInput1() )
{
InputImage1Pointer image1 =
const_cast< InputImage1Type * >( this->GetInput1() );
image1->SetRequestedRegionToLargestPossibleRegion();
if ( this->GetInput2() )
{
InputImage2Pointer image2 =
const_cast< InputImage2Type * >( this->GetInput2() );
image2->SetRequestedRegion(
this->GetInput1()->GetRequestedRegion() );
}
}
}
template<class TInputImage1, class TInputImage2>
void
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::EnlargeOutputRequestedRegion(DataObject *data)
{
Superclass::EnlargeOutputRequestedRegion(data);
data->SetRequestedRegionToLargestPossibleRegion();
}
template<class TInputImage1, class TInputImage2>
void
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::AllocateOutputs()
{
// Pass the first input through as the output
InputImage1Pointer image =
const_cast< TInputImage1 * >( this->GetInput1() );
this->GraftOutput( image );
}
template<class TInputImage1, class TInputImage2>
void
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::BeforeThreadedGenerateData()
{
int numberOfThreads = this->GetNumberOfThreads();
// Resize the thread temporaries
m_MaxDistance.SetSize(numberOfThreads);
// Initialize the temporaries
m_MaxDistance.Fill(NumericTraits<RealType>::Zero);
// Compute Danielsson distance from non-zero pixels in the second image
typedef itk::DanielssonDistanceMapImageFilter<InputImage2Type,DistanceMapType>
FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( this->GetInput2() );
filter->Update();
m_DistanceMap = filter->GetOutput();
}
template<class TInputImage1, class TInputImage2>
void
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::AfterThreadedGenerateData()
{
int i;
int numberOfThreads = this->GetNumberOfThreads();
m_DirectedHausdorffDistance = NumericTraits<RealType>::Zero;
// find max over all threads
for( i = 0; i < numberOfThreads; i++)
{
if ( m_MaxDistance[i] > m_DirectedHausdorffDistance )
{
m_DirectedHausdorffDistance = m_MaxDistance[i];
}
}
// clean up
m_DistanceMap = NULL;
}
template<class TInputImage1, class TInputImage2>
void
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::ThreadedGenerateData(const RegionType& regionForThread,
int threadId)
{
ImageRegionConstIterator<TInputImage1> it1 (this->GetInput1(), regionForThread);
ImageRegionConstIterator<DistanceMapType> it2 (m_DistanceMap, regionForThread);
// support progress methods/callbacks
ProgressReporter progress(this, threadId, regionForThread.GetNumberOfPixels());
// do the work
while (!it1.IsAtEnd())
{
if( it1.Get() != NumericTraits<InputImage1PixelType>::Zero )
{
if ( it2.Get() > m_MaxDistance[threadId] )
{
m_MaxDistance[threadId] = it2.Get();
}
}
++it1;
++it2;
progress.CompletedPixel();
}
}
template<class TInputImage1, class TInputImage2>
void
DirectedHausdorffDistanceImageFilter<TInputImage1, TInputImage2>
::PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os,indent);
os << indent << "DirectedHausdorffDistance: "
<< m_DirectedHausdorffDistance << std::endl;
}
}// end namespace itk
#endif
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