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/*=========================================================================
Program: ORFEO Toolbox
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt 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 otbGenericRoadExtractionFilter_txx
#define otbGenericRoadExtractionFilter_txx
#include "otbGenericRoadExtractionFilter.h"
#include "otbMath.h"
namespace otb
{
/**
* Constructor
*/
template <class TInputImage, class TOutputPath>
GenericRoadExtractionFilter<TInputImage, TOutputPath>
::GenericRoadExtractionFilter()
{
this->SetNumberOfRequiredInputs(1);
this->SetNumberOfRequiredOutputs(1);
m_SquareRootImageFilter = SquareRootImageFilterType::New();
m_GradientFilter = GradientFilterType::New();
m_NeighborhoodScalarProductFilter = NeighborhoodScalarProductFilterType::New();
m_RemoveIsolatedByDirectionFilter = RemoveIsolatedByDirectionFilterType::New();
m_RemoveWrongDirectionFilter = RemoveWrongDirectionFilterType::New();
m_NonMaxRemovalByDirectionFilter = NonMaxRemovalByDirectionFilterType::New();
m_VectorizationPathListFilter = VectorizationPathListFilterType::New();
m_FirstSimplifyPathListFilter = SimplifyPathListFilterType::New();
m_SecondSimplifyPathListFilter = SimplifyPathListFilterType::New();
m_BreakAngularPathListFilter = BreakAngularPathListFilterType::New();
m_FirstRemoveTortuousPathListFilter = RemoveTortuousPathListFilterType::New();
m_SecondRemoveTortuousPathListFilter = RemoveTortuousPathListFilterType::New();
m_LinkPathListFilter = LinkPathListFilterType::New();
m_LikelihoodPathListFilter = LikelihoodPathListFilterType::New();
/** Amplitude threshold to start following a path (use by the VectorizationPathListFilter)*/
m_AmplitudeThreshold = static_cast<AmplitudeThresholdType>(0.00005);
/** Tolerance for segment consistency (tolerance in terms of distance) (use by the SimplifyPathFilter)*/
m_Tolerance = static_cast<ToleranceType>(1.);
/** Max angle (use bye the BreakAngularPathListFilter)*/
m_MaxAngle = static_cast<MaxAngleType>(CONST_PI_8);
/** Tolerance for segment consistency (tolerance in terms of distance) (use by RemoveTortuousPathFilter)*/
m_FirstMeanDistanceThreshold = static_cast<MeanDistanceThresholdType>(1.);
m_SecondMeanDistanceThreshold = static_cast<MeanDistanceThresholdType>(10.);
/** The angular threshold (use by LinkPathFilter) */
m_AngularThreshold = static_cast<LinkRealType>(CONST_PI_8);
/** The distance threshold (use by LinkPathFilter) */
m_DistanceThreshold = 25.;
/** Alpha value */
/** Use to calculate the sigma value use by the GradientRecursiveGaussianImageFilter */
m_Alpha = 1.0;
/** Resolution of the image */
m_Resolution = 1.;
}
/**
* Prepare main computation method
*/
template <class TInputImage, class TOutputPath>
void
GenericRoadExtractionFilter<TInputImage, TOutputPath>
::BeforeGenerateData()
{
/** Calculation of resolution value */
typename InputImageType::SpacingType spacing = this->GetInput()->GetSpacing();
// Getting x Spacing for the resolution
m_Resolution = static_cast<double>(spacing[0]);
if (m_Resolution == 0.)
{
itkWarningMacro(<< "The image spacing is zero. So the resolution used in the filter is forced to 1.");
m_Resolution = 1.;
}
}
/**
* Main computation method
*/
template <class TInputImage, class TOutputPath>
void
GenericRoadExtractionFilter<TInputImage, TOutputPath>
::GenerateData()
{
// // Input images pointers
typename InputImageType::ConstPointer inputImage = this->GetInput();
typename OutputPathListType::Pointer outputPathList = this->GetOutput();
///////////////////////////////////////
//// Algorithm for road extraction ////
///////////////////////////////////////
//
m_SquareRootImageFilter->SetInput(inputImage);
m_GradientFilter->SetInput(m_SquareRootImageFilter->GetOutput());
/** Sigma calculated with the alpha and image resolution parameters */
m_GradientFilter->SetSigma(static_cast<SigmaType>(m_Alpha * (1.2 / m_Resolution + 1.)));
m_GradientFilter->SetUseImageDirection(false);
m_NeighborhoodScalarProductFilter->SetInput(m_GradientFilter->GetOutput());
m_RemoveIsolatedByDirectionFilter->SetInput(m_NeighborhoodScalarProductFilter->GetOutput());
m_RemoveIsolatedByDirectionFilter->SetInputDirection(m_NeighborhoodScalarProductFilter->GetOutputDirection());
m_RemoveWrongDirectionFilter->SetInput(m_RemoveIsolatedByDirectionFilter->GetOutput());
m_RemoveWrongDirectionFilter->SetInputDirection(m_NeighborhoodScalarProductFilter->GetOutputDirection());
m_NonMaxRemovalByDirectionFilter->SetInput(m_RemoveWrongDirectionFilter->GetOutput());
m_NonMaxRemovalByDirectionFilter->SetInputDirection(m_NeighborhoodScalarProductFilter->GetOutputDirection());
m_VectorizationPathListFilter->SetInput(m_NonMaxRemovalByDirectionFilter->GetOutput());
m_VectorizationPathListFilter->SetInputDirection(m_NeighborhoodScalarProductFilter->GetOutputDirection());
m_VectorizationPathListFilter->SetAmplitudeThreshold(m_AmplitudeThreshold);
m_FirstSimplifyPathListFilter->SetInput(m_VectorizationPathListFilter->GetOutput());
m_FirstSimplifyPathListFilter->GetFunctor().SetTolerance(m_Tolerance);
m_BreakAngularPathListFilter->SetInput(m_FirstSimplifyPathListFilter->GetOutput());
m_BreakAngularPathListFilter->SetMaxAngle(m_MaxAngle);
m_FirstRemoveTortuousPathListFilter->SetInput(m_BreakAngularPathListFilter->GetOutput());
m_FirstRemoveTortuousPathListFilter->GetFunctor().SetThreshold(m_FirstMeanDistanceThreshold);
m_LinkPathListFilter->SetInput(m_FirstRemoveTortuousPathListFilter->GetOutput());
m_LinkPathListFilter->SetAngularThreshold(m_AngularThreshold);
m_LinkPathListFilter->SetDistanceThreshold(static_cast<LinkRealType>(m_DistanceThreshold / m_Resolution));
m_SecondSimplifyPathListFilter->SetInput(m_LinkPathListFilter->GetOutput());
m_SecondSimplifyPathListFilter->GetFunctor().SetTolerance(m_Tolerance);
m_SecondRemoveTortuousPathListFilter->SetInput(m_SecondSimplifyPathListFilter->GetOutput());
m_SecondRemoveTortuousPathListFilter->GetFunctor().SetThreshold(m_SecondMeanDistanceThreshold);
m_LikelihoodPathListFilter->SetInput(m_SecondRemoveTortuousPathListFilter->GetOutput());
m_LikelihoodPathListFilter->SetInputImage(m_NonMaxRemovalByDirectionFilter->GetOutput());
// Graft output seems to be broken for PolylineParametricPath
// So we use update, and copy the path to the output path list.
// m_LikelihoodPathListFilter->GraftOutput(this->GetOutput());
m_LikelihoodPathListFilter->Update();
// outputPathList = m_LikelihoodPathListFilter->GetOutput();
for (typename LikelihoodPathListFilterType::PathListType::ConstIterator it
= m_LikelihoodPathListFilter->GetOutput()->Begin();
it != m_LikelihoodPathListFilter->GetOutput()->End();
++it)
{
outputPathList->PushBack(it.Get());
}
}
/**
* PrintSelf method
*/
template <class TInputImage, class TOutputPath>
void
GenericRoadExtractionFilter<TInputImage, TOutputPath>
::PrintSelf(std::ostream& os, itk::Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "m_Alpha:" << m_Alpha << std::endl;
os << indent << "m_Resolution:" << m_Resolution << std::endl;
os << indent << "m_AmplitudeThreshold: " << m_AmplitudeThreshold << std::endl;
os << indent << "m_Tolerance: " << m_Tolerance << std::endl;
os << indent << "m_MaxAngle: " << m_MaxAngle << std::endl;
os << indent << "m_FirstMeanDistanceThreshold: " << m_FirstMeanDistanceThreshold << std::endl;
os << indent << "m_SecondMeanDistanceThreshold: " << m_SecondMeanDistanceThreshold << std::endl;
os << indent << "m_DistanceThreshold: " << m_DistanceThreshold << std::endl;
os << indent << "m_AngularThreshold: " << m_AngularThreshold << std::endl;
}
} // End namespace otb
#endif
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