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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 "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkPointSet.h"
#include "itkBSplineScatteredDataPointSetToImageFilter.h"
#include "itkTestingMacros.h"
/**
* In this test, we approximate a 2-D scalar field.
* The scattered data is derived from a segmented
* image. We write the output to an image for
* comparison.
*/
int itkBSplineScatteredDataPointSetToImageFilterTest( int argc, char * argv [] )
{
if ( argc != 3 )
{
std::cout << "Usage: " << argv[0] << " inputImage outputImage" << std::endl;
return EXIT_FAILURE;
}
const unsigned int ParametricDimension = 2;
const unsigned int DataDimension = 1;
typedef int PixelType;
typedef itk::Image<PixelType, ParametricDimension> InputImageType;
typedef float RealType;
typedef itk::Vector<RealType, DataDimension> VectorType;
typedef itk::Image<VectorType, ParametricDimension> VectorImageType;
typedef itk::PointSet <VectorImageType::PixelType,
ParametricDimension> PointSetType;
PointSetType::Pointer pointSet = PointSetType::New();
typedef itk::ImageFileReader<InputImageType> ReaderType;
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( argv[1] );
reader->Update();
itk::ImageRegionIteratorWithIndex<InputImageType>
It( reader->GetOutput(), reader->GetOutput()->GetLargestPossibleRegion() );
// Iterate through the input image which consists of multivalued
// foreground pixels (=nonzero) and background values (=zero).
// The foreground pixels comprise the input point set.
for ( It.GoToBegin(); !It.IsAtEnd(); ++It )
{
if ( It.Get() != itk::NumericTraits<PixelType>::ZeroValue() )
{
// We extract both the 2-D location of the point
// and the pixel value of that point.
PointSetType::PointType point;
reader->GetOutput()->TransformIndexToPhysicalPoint( It.GetIndex(), point );
unsigned long i = pointSet->GetNumberOfPoints();
pointSet->SetPoint( i, point );
PointSetType::PixelType V( DataDimension );
V[0] = static_cast<RealType>( It.Get() );
pointSet->SetPointData( i, V );
}
}
// Instantiate the B-spline filter and set the desired parameters.
typedef itk::BSplineScatteredDataPointSetToImageFilter
<PointSetType, VectorImageType> FilterType;
FilterType::Pointer filter = FilterType::New();
EXERCISE_BASIC_OBJECT_METHODS( filter, BSplineScatteredDataPointSetToImageFilter,
PointSetToImageFilter );
unsigned int splineOrder = 0u;
TRY_EXPECT_EXCEPTION( filter->SetSplineOrder( splineOrder ) );
FilterType::ArrayType splineOrderArray;
splineOrderArray.Fill( 4u );
filter->SetSplineOrder( splineOrderArray );
TEST_SET_GET_VALUE( splineOrderArray, filter->GetSplineOrder() );
splineOrder = 3u;
filter->SetSplineOrder( splineOrder );
splineOrderArray.Fill( splineOrder );
TEST_SET_GET_VALUE( splineOrderArray, filter->GetSplineOrder() );
unsigned numberOfLevels = 0u;
TRY_EXPECT_EXCEPTION( filter->SetNumberOfLevels( numberOfLevels ) );
FilterType::ArrayType numberOfLevelsArray;
numberOfLevelsArray.Fill( 4u );
filter->SetNumberOfLevels( numberOfLevelsArray );
TEST_SET_GET_VALUE( numberOfLevelsArray, filter->GetNumberOfLevels() );
numberOfLevels = 3u;
filter->SetNumberOfLevels( numberOfLevels );
numberOfLevelsArray.Fill( numberOfLevels );
TEST_SET_GET_VALUE( numberOfLevelsArray, filter->GetNumberOfLevels() );
FilterType::ArrayType ncps;
ncps.Fill( 4u );
filter->SetNumberOfControlPoints( ncps );
TEST_SET_GET_VALUE( ncps, filter->GetNumberOfControlPoints() );
FilterType::ArrayType close;
close.Fill( 0u );
filter->SetCloseDimension( close );
TEST_SET_GET_VALUE( close, filter->GetCloseDimension() );
// Define the parametric domain.
filter->SetOrigin( reader->GetOutput()->GetOrigin() );
filter->SetSpacing( reader->GetOutput()->GetSpacing() );
filter->SetSize( reader->GetOutput()->GetLargestPossibleRegion().GetSize() );
filter->SetDirection( reader->GetOutput()->GetDirection() );
filter->SetInput( pointSet );
TRY_EXPECT_NO_EXCEPTION( filter->Update() );
// Get the current number of control points to increase coverage
std::cout << "Current number of control points: "
<< filter->GetCurrentNumberOfControlPoints() << std::endl;
// Get the control point lattice produced by the fitting process to increase
// coverage
std::cout << "Control point lattice produced by the fitting process: " << std::endl;
std::cout << filter->GetPhiLattice() << std::endl;
VectorImageType *outputImage = filter->GetOutput();
// Write the output to an image.
typedef itk::Image<RealType, ParametricDimension> RealImageType;
RealImageType::Pointer image = RealImageType::New();
image->SetRegions( reader->GetOutput()->GetLargestPossibleRegion() );
image->Allocate();
itk::ImageRegionIteratorWithIndex<RealImageType>
Itt( image, image->GetLargestPossibleRegion() );
for ( Itt.GoToBegin(); !Itt.IsAtEnd(); ++Itt )
{
Itt.Set( outputImage->GetPixel( Itt.GetIndex() )[0] );
}
typedef itk::ImageFileWriter<RealImageType> WriterType;
WriterType::Pointer writer = WriterType::New();
writer->SetInput( image );
writer->SetFileName( argv[2] );
TRY_EXPECT_NO_EXCEPTION( writer->Update() );
return EXIT_SUCCESS;
}
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