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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.
*
*=========================================================================*/
#include "itkSparseFieldFourthOrderLevelSetImageFilter.h"
#include <iostream>
/*
* This test exercises the SparseFieldFourthOrderLevelSetImageFilter
* framework. A 2D image of a square is created and passed as input to the
* filter which performs 500 iterations. This application will perform
* isotropic fourth order diffusion on the input; therefore, the square will
* morph towards a circle. The classes tested are the following:
*
* SparseImage
* FiniteDifferenceSparseImageFilter
* FiniteDifferenceSparseImageFunction
* ImplicitManifoldNormalDiffusionFilter
* NormalVectorFunctionBase
* NormalVectorDiffusionFunction
* LevelSetFunctionWithRefitTerm
* SparseFieldFourthOrderLevelSetImageFilter
*
*/
namespace SFFOLSIFT { // local namespace for helper functions
const unsigned int HEIGHT = (128);
const unsigned int WIDTH = (128);
#define RADIUS (std::min(HEIGHT, WIDTH)/4)
// Distance transform function for square
float square(unsigned x, unsigned y)
{
float X, Y;
X = std::fabs(x - (float)WIDTH/2.0);
Y = std::fabs(y - (float)HEIGHT/2.0);
float dis;
if (!((X > RADIUS)&&(Y > RADIUS)))
dis = RADIUS - std::max(X, Y);
else
dis = -std::sqrt((X - RADIUS)*(X - RADIUS) + (Y - RADIUS)*(Y - RADIUS));
return(dis);
}
// Evaluates a function at each pixel in the itk image
void evaluate_function(itk::Image<float, 2> *im,
float (*f)(unsigned int, unsigned int) )
{
itk::Image<float, 2>::IndexType idx;
for (unsigned int x = 0; x < WIDTH; ++x)
{
idx[0] = x;
for (unsigned int y = 0; y < HEIGHT; ++y)
{
idx[1] = y;
im->SetPixel(idx, f(x, y) );
}
}
}
} // end namespace
namespace itk {
template <typename TInputImage, typename TOutputImage>
class IsotropicDiffusionLevelSetFilter
: public SparseFieldFourthOrderLevelSetImageFilter <TInputImage, TOutputImage>
{
public:
typedef IsotropicDiffusionLevelSetFilter Self;
typedef SparseFieldFourthOrderLevelSetImageFilter <TInputImage,
TOutputImage>
Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
itkTypeMacro(IsotropicDiffusionLevelSetFilter,SparseFieldFourthOrderLevelSetImageFilter);
itkNewMacro (Self);
typedef typename Superclass::SparseImageType SparseImageType;
typedef LevelSetFunctionWithRefitTerm <TOutputImage,SparseImageType> FunctionType;
typedef typename FunctionType::RadiusType RadiusType;
protected:
typename FunctionType::Pointer m_Function;
IsotropicDiffusionLevelSetFilter()
{
RadiusType radius;
for (unsigned int j=0; j<TInputImage::ImageDimension;j++)
{
radius[j] = 1;
}
m_Function=FunctionType::New();
this->SetLevelSetFunction(m_Function);
this->SetNumberOfLayers(this->GetMinimumNumberOfLayers());
this->SetMaxNormalIteration(10);
this->SetMaxRefitIteration(40);
m_Function->Initialize(radius);
this->SetNormalProcessType (0);
m_Function->Print(std::cout);
}
virtual bool Halt () ITK_OVERRIDE
{
if (this->GetElapsedIterations() == 50)
{
return true;
}
else
{
return false;
}
}
};
} // end namespace itk
int itkSparseFieldFourthOrderLevelSetImageFilterTest(int, char* [] )
{
typedef itk::Image<float, 2> ImageType;
ImageType::Pointer im_init = ImageType::New();
ImageType::RegionType r;
ImageType::SizeType sz = {{SFFOLSIFT::HEIGHT, SFFOLSIFT::WIDTH}};
ImageType::IndexType idx = {{0,0}};
r.SetSize(sz);
r.SetIndex(idx);
im_init->SetLargestPossibleRegion(r);
im_init->SetBufferedRegion(r);
im_init->SetRequestedRegion(r);
im_init->Allocate();
SFFOLSIFT::evaluate_function(im_init, SFFOLSIFT::square);
typedef itk::IsotropicDiffusionLevelSetFilter<ImageType, ImageType> FilterType;
FilterType::Pointer filter = FilterType::New();
filter->SetInput(im_init);
std::cout<<"MaxRefitIteration = "<<(filter->GetMaxRefitIteration())<<"\n";
std::cout<<"MaxNormalIteration = "<<(filter->GetMaxNormalIteration())<<"\n";
filter->SetCurvatureBandWidth (4);
std::cout<<"CurvatureBandWidth= "<<(filter->GetCurvatureBandWidth())<<"\n";
filter->SetRMSChangeNormalProcessTrigger(0.001);
std::cout<<"RMS change trigger = "
<<(filter->GetRMSChangeNormalProcessTrigger())<<"\n";
std::cout<<"Normal process type = "<<(filter->GetNormalProcessType())<<"\n";
std::cout<<"Conductance = "<<(filter->GetNormalProcessConductance())<<"\n";
std::cout<<"Unsharp flag = "<<(filter->GetNormalProcessUnsharpFlag())<<"\n";
std::cout<<"Unsharp weight = "
<<(filter->GetNormalProcessUnsharpWeight())<<"\n";
filter->Update();
filter->Print(std::cout);
std::cout<<"Passed.\n";
return EXIT_SUCCESS;
}
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