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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.
*
*=========================================================================*/
// Software Guide : BeginLatex
//
// This example illustrates the use of Mathematical Morphology filters for
// image enhancement. One of the difficulties of image enhancement is that it
// is defined based on human visual perception and it is related to a
// particular set of features that are of interest in the image. In this
// context, what is considered enhancement for one person, may be seen as
// image degradation by another person.
//
// \index{itk::AntiAliasBinaryImageFilter|textbf}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkImage.h"
#include "itkPNGImageIO.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkGrayscaleMorphologicalOpeningImageFilter.h"
#include "itkGrayscaleMorphologicalClosingImageFilter.h"
#include "itkBinaryBallStructuringElement.h"
#include "itkConstrainedValueAdditionImageFilter.h"
#include "itkConstrainedValueDifferenceImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
int
main(int argc, char * argv[])
{
if (argc < 4)
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile ";
std::cerr << " outputImageFile radius " << std::endl;
return EXIT_FAILURE;
}
//
// The following code defines the input and output pixel types and their
// associated image types.
//
constexpr unsigned int Dimension = 2;
using PixelType = unsigned char;
using WritePixelType = unsigned char;
using ImageType = itk::Image<PixelType, Dimension>;
using WriteImageType = itk::Image<WritePixelType, Dimension>;
// readers/writers
using ReaderType = itk::ImageFileReader<ImageType>;
using WriterType = itk::ImageFileWriter<WriteImageType>;
// structuring element
using StructuringElementType =
itk::BinaryBallStructuringElement<PixelType, Dimension>;
// define the opening and closing types
using OpeningFilterType =
itk::GrayscaleMorphologicalOpeningImageFilter<ImageType,
ImageType,
StructuringElementType>;
using ClosingFilterType =
itk::GrayscaleMorphologicalClosingImageFilter<ImageType,
ImageType,
StructuringElementType>;
// define arithmetic operation filters
using AdditionFilterType =
itk::ConstrainedValueAdditionImageFilter<ImageType, ImageType, ImageType>;
using SubtractionFilterType = itk::
ConstrainedValueDifferenceImageFilter<ImageType, ImageType, ImageType>;
// define rescaling filter
using RescaleFilterType =
itk::RescaleIntensityImageFilter<ImageType, WriteImageType>;
// Create structuring element
StructuringElementType structuringElement;
// (argv[3]+1) x (argv[3]+1) structuring element
structuringElement.SetRadius(std::stoi(argv[3]));
structuringElement.CreateStructuringElement();
// Setup the input and output files
auto reader = ReaderType::New();
reader->SetFileName(argv[1]);
auto writer = WriterType::New();
writer->SetFileName(argv[2]);
// reading input image
try
{
reader->Update();
}
catch (const itk::ExceptionObject & err)
{
std::cout << "Problems reading input image" << std::endl;
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
// Create the opening closing filters
auto opening = OpeningFilterType::New();
auto closing = ClosingFilterType::New();
// Setup the opening and closing methods
opening->SetKernel(structuringElement);
closing->SetKernel(structuringElement);
// Setup minimum and maximum of rescale filter
auto rescaleFilter = RescaleFilterType::New();
rescaleFilter->SetOutputMinimum(0);
rescaleFilter->SetOutputMaximum(255);
// creation of the pipeline. The enhancement operation is given by:
// Original Image + Top Hat Image - Bottom Hat Image
opening->SetInput(reader->GetOutput());
closing->SetInput(reader->GetOutput());
auto topHat = SubtractionFilterType::New();
topHat->SetInput1(reader->GetOutput());
topHat->SetInput2(opening->GetOutput());
auto bottomHat = SubtractionFilterType::New();
bottomHat->SetInput1(closing->GetOutput());
bottomHat->SetInput2(reader->GetOutput());
auto internalAddition = AdditionFilterType::New();
internalAddition->SetInput1(reader->GetOutput());
internalAddition->SetInput2(topHat->GetOutput());
auto imageEnhancement = SubtractionFilterType::New();
imageEnhancement->SetInput1(internalAddition->GetOutput());
imageEnhancement->SetInput2(bottomHat->GetOutput());
rescaleFilter->SetInput(imageEnhancement->GetOutput());
writer->SetInput(rescaleFilter->GetOutput());
try
{
writer->Update();
}
catch (const itk::ExceptionObject & err)
{
std::cout << "ExceptionObject caught !" << std::endl;
std::cout << err << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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