Examples/Filtering/MorphologicalImageEnhancement.cxx

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 *  Copyright Insight Software Consortium
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 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
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//  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
  ReaderType::Pointer reader = ReaderType::New();
  reader->SetFileName( argv[1] );
  WriterType::Pointer writer  = WriterType::New();
  writer->SetFileName( argv[2] );

  // reading input image
  try
    {
    reader->Update();
    }
  catch ( 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
  OpeningFilterType::Pointer  opening  = OpeningFilterType::New();
  ClosingFilterType::Pointer  closing  = ClosingFilterType::New();
  // Setup the opening and closing methods
  opening->SetKernel(  structuringElement );
  closing->SetKernel(  structuringElement );
  // Setup minnimum and maximum of rescale filter
  RescaleFilterType::Pointer 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()           );
  SubtractionFilterType::Pointer topHat    = SubtractionFilterType::New();
  topHat->SetInput1(           reader->GetOutput()           );
  topHat->SetInput2(           opening->GetOutput()          );
  SubtractionFilterType::Pointer bottomHat = SubtractionFilterType::New();
  bottomHat->SetInput1(        closing->GetOutput()          );
  bottomHat->SetInput2(        reader->GetOutput()           );
  AdditionFilterType::Pointer    internalAddition = AdditionFilterType::New();
  internalAddition->SetInput1( reader->GetOutput()           );
  internalAddition->SetInput2( topHat->GetOutput()           );

  SubtractionFilterType::Pointer imageEnhancement =
                                                 SubtractionFilterType::New();
  imageEnhancement->SetInput1( internalAddition->GetOutput() );
  imageEnhancement->SetInput2( bottomHat->GetOutput()        );
  rescaleFilter->SetInput(     imageEnhancement->GetOutput() );
  writer->SetInput(            rescaleFilter->GetOutput()    );
  try
    {
    writer->Update();
    }
  catch( itk::ExceptionObject & err )
    {
    std::cout << "ExceptionObject caught !" << std::endl;
    std::cout << err <<std::endl;
    return EXIT_FAILURE;
    }
  return EXIT_SUCCESS;
}