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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 <fstream>
#include "itkBilateralImageFilter.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkSimpleFilterWatcher.h"
#include "itkTestingMacros.h"
int
itkBilateralImageFilterTest2(int argc, char * argv[])
{
if (argc < 3)
{
std::cerr << "Missing parameters." << std::endl;
std::cerr << "Usage: " << itkNameOfTestExecutableMacro(argv) << " InputImage OutputImage" << std::endl;
return EXIT_FAILURE;
}
using PixelType = unsigned char;
constexpr unsigned int dimension = 2;
using myImage = itk::Image<PixelType, dimension>;
itk::ImageFileReader<myImage>::Pointer input = itk::ImageFileReader<myImage>::New();
input->SetFileName(argv[1]);
// Create a filter
using FilterType = itk::BilateralImageFilter<myImage, myImage>;
auto filter = FilterType::New();
itk::SimpleFilterWatcher watcher(filter, "filter");
filter->SetInput(input->GetOutput());
// these settings reduce the amount of noise by a factor of 10
// when the original signal to noise level is 5
auto domainSigmaValue = 4.0;
filter->SetDomainSigma(domainSigmaValue);
auto domainSigma = filter->GetDomainSigma();
for (auto & value : domainSigma)
{
auto index = &value - &*(domainSigma.begin());
ITK_TEST_SET_GET_VALUE(domainSigmaValue, filter->GetDomainSigma()[index]);
}
double domainSigmaArr[dimension];
for (double & i : domainSigmaArr)
{
i = domainSigmaValue;
}
filter->SetDomainSigma(domainSigmaArr);
for (auto & value : domainSigmaArr)
{
auto index = &value - &domainSigmaArr[0];
ITK_TEST_SET_GET_VALUE(value, filter->GetDomainSigma()[index]);
}
auto rangeSigma = 50.0;
filter->SetRangeSigma(rangeSigma);
ITK_TEST_SET_GET_VALUE(rangeSigma, filter->GetRangeSigma());
auto domainMu = 2.5;
filter->SetDomainMu(domainMu);
ITK_TEST_SET_GET_VALUE(domainMu, filter->GetDomainMu());
unsigned int filterDimensionality = dimension;
filter->SetFilterDimensionality(filterDimensionality);
ITK_TEST_SET_GET_VALUE(filterDimensionality, filter->GetFilterDimensionality());
unsigned long numberOfRangeGaussianSamples = 100;
filter->SetNumberOfRangeGaussianSamples(numberOfRangeGaussianSamples);
ITK_TEST_SET_GET_VALUE(numberOfRangeGaussianSamples, filter->GetNumberOfRangeGaussianSamples());
ITK_TRY_EXPECT_NO_EXCEPTION(input->Update());
ITK_TRY_EXPECT_NO_EXCEPTION(filter->Update());
// Generate test image
itk::ImageFileWriter<myImage>::Pointer writer;
writer = itk::ImageFileWriter<myImage>::New();
writer->SetInput(filter->GetOutput());
writer->SetFileName(argv[2]);
ITK_TRY_EXPECT_NO_EXCEPTION(writer->Update());
std::cout << "Test finished." << std::endl;
return EXIT_SUCCESS;
}
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