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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.
*
*=========================================================================*/
//
// This example was originally contributed by Stephan in the users list
//
// https://public.kitware.com/pipermail/insight-users/2005-June/013482.html
//
//
// Software Guide : BeginLatex
//
// This example illustrates how to compute the direct Fourier transform
// followed by the inverse Fourier transform in order to recover the original
// data.
//
// Software Guide : EndLatex
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkResampleImageFilter.h"
#include "itkVnlForwardFFTImageFilter.h"
#include "itkVnlInverseFFTImageFilter.h"
int
main(int argc, char * argv[])
{
if (argc != 3)
{
std::cerr << "Usage: " << argv[0] << " input output" << std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// First we set up the types of the input and output images.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
constexpr unsigned int Dimension = 2;
using IOPixelType = unsigned short;
using WorkPixelType = float;
using IOImageType = itk::Image<IOPixelType, Dimension>;
using WorkImageType = itk::Image<WorkPixelType, Dimension>;
// Software Guide : EndCodeSnippet
// File handling
using ReaderType = itk::ImageFileReader<IOImageType>;
using WriterType = itk::ImageFileWriter<IOImageType>;
auto inputreader = ReaderType::New();
auto writer = WriterType::New();
inputreader->SetFileName(argv[1]);
writer->SetFileName(argv[2]);
// Handle padding of the image with resampling
using ResamplerType = itk::ResampleImageFilter<IOImageType, WorkImageType>;
auto inputresampler = ResamplerType::New();
inputresampler->SetDefaultPixelValue(0);
// Read the image and get its size
inputreader->Update();
IOImageType::SizeType inputsize;
IOImageType::SizeType worksize;
inputsize = inputreader->GetOutput()->GetLargestPossibleRegion().GetSize();
// worksize is the nearest multiple of 2 larger than the input
for (unsigned int i = 0; i < 2; ++i)
{
unsigned int n = 0;
worksize[i] = inputsize[i];
while (worksize[i] >>= 1)
{
n++;
}
worksize[i] = static_cast<IOImageType::SizeValueType>(1)
<< static_cast<IOImageType::SizeValueType>(n + 1);
std::cout << "inputsize[" << i << "]=" << inputsize[i] << std::endl;
std::cout << "worksize[" << i << "]=" << worksize[i] << std::endl;
}
inputresampler->SetSize(worksize);
inputresampler->SetInput(inputreader->GetOutput());
// Forward FFT filter
using FFTFilterType = itk::VnlForwardFFTImageFilter<WorkImageType>;
auto fftinput = FFTFilterType::New();
fftinput->SetInput(inputresampler->GetOutput());
// This is the output type from the FFT filters
using ComplexImageType = FFTFilterType::OutputImageType;
// Do the inverse transform = forward transform / num voxels
using invFFTFilterType = itk::VnlInverseFFTImageFilter<ComplexImageType>;
auto fftoutput = invFFTFilterType::New();
fftoutput->SetInput(
fftinput->GetOutput()); // try to recover the input image
// undo the padding
using ResampleOutType =
itk::ResampleImageFilter<WorkImageType, IOImageType>;
auto outputResampler = ResampleOutType::New();
outputResampler->SetDefaultPixelValue(0);
outputResampler->SetSize(inputsize);
outputResampler->SetInput(fftoutput->GetOutput());
// Write the output
writer->SetInput(outputResampler->GetOutput());
writer->Update();
return EXIT_SUCCESS;
}
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