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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 "itkConstantBoundaryCondition.h"
#include "itkInverseDeconvolutionImageFilter.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkTestingMacros.h"
int
itkInverseDeconvolutionImageFilterTest(int argc, char * argv[])
{
if (argc < 4)
{
std::cout << "Usage: " << itkNameOfTestExecutableMacro(argv)
<< " inputImage kernelImage outputImage [normalizeImage]" << std::endl;
return EXIT_FAILURE;
}
constexpr int ImageDimension = 2;
using PixelType = float;
using ImageType = itk::Image<PixelType, ImageDimension>;
using ReaderType = itk::ImageFileReader<ImageType>;
auto reader1 = ReaderType::New();
reader1->SetFileName(argv[1]);
reader1->Update();
auto reader2 = ReaderType::New();
reader2->SetFileName(argv[2]);
reader2->Update();
itk::ConstantBoundaryCondition<ImageType> cbc;
cbc.SetConstant(0.0);
using ConvolutionFilterType = itk::FFTConvolutionImageFilter<ImageType>;
auto convolutionFilter = ConvolutionFilterType::New();
convolutionFilter->SetInput(reader1->GetOutput());
convolutionFilter->SetKernelImage(reader2->GetOutput());
convolutionFilter->SetBoundaryCondition(&cbc);
// Use the same SizeGreatestPrimeFactor across FFT backends to get
// consistent results.
convolutionFilter->SetSizeGreatestPrimeFactor(5);
bool normalize = false;
if (argc >= 5)
{
normalize = static_cast<bool>(std::stoi(argv[4]));
}
convolutionFilter->SetNormalize(normalize);
using DeconvolutionFilterType = itk::InverseDeconvolutionImageFilter<ImageType>;
auto deconvolutionFilter = DeconvolutionFilterType::New();
deconvolutionFilter->SetInput(convolutionFilter->GetOutput());
deconvolutionFilter->SetKernelImage(reader2->GetOutput());
deconvolutionFilter->SetNormalize(normalize);
deconvolutionFilter->SetBoundaryCondition(&cbc);
deconvolutionFilter->SetSizeGreatestPrimeFactor(5);
// Check default KernelZeroMagnitudeThreshold value
ITK_TEST_SET_GET_VALUE(1.0e-4, deconvolutionFilter->GetKernelZeroMagnitudeThreshold());
double zeroMagnitudeThreshold = 1.0e-2;
deconvolutionFilter->SetKernelZeroMagnitudeThreshold(zeroMagnitudeThreshold);
ITK_TEST_SET_GET_VALUE(zeroMagnitudeThreshold, deconvolutionFilter->GetKernelZeroMagnitudeThreshold());
using WriterType = itk::ImageFileWriter<ImageType>;
auto writer = WriterType::New();
writer->SetFileName(argv[3]);
writer->SetInput(deconvolutionFilter->GetOutput());
try
{
writer->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << excp << std::endl;
return EXIT_FAILURE;
}
deconvolutionFilter->Print(std::cout);
// Instantiate types with non-default template parameters
using FloatImageType = itk::Image<float, ImageDimension>;
using DoubleImageType = itk::Image<double, ImageDimension>;
using IntImageType = itk::Image<int, ImageDimension>;
using FilterType = itk::InverseDeconvolutionImageFilter<FloatImageType, DoubleImageType, IntImageType, float>;
auto filter = FilterType::New();
filter->Print(std::cout);
return EXIT_SUCCESS;
}
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