Examples/Filtering/DanielssonDistanceMapImageFilter.cxx

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//  Software Guide : BeginCommandLineArgs
//    INPUTS:  {FivePointsDilated.png}
//    OUTPUTS: {DanielssonDistanceMapImageFilterOutput1.png}
//    OUTPUTS: {DanielssonDistanceMapImageFilterOutput2.png}
//    ARGUMENTS: {DanielssonDistanceMapImageFilterOutput3.mhd}
//  Software Guide : EndCommandLineArgs
 
// Software Guide : BeginLatex
//
// This example illustrates the use of the
// \doxygen{DanielssonDistanceMapImageFilter}.  This filter generates a
// distance map from the input image using the algorithm developed by
// Danielsson \cite{Danielsson1980}. As secondary outputs, a Voronoi
// partition of the input elements is produced, as well as a vector image
// with the components of the distance vector to the closest point. The input
// to the map is assumed to be a set of points on the input image. The label
// of each group of pixels is assigned by the
// \doxygen{ConnectedComponentImageFilter}.
//
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!Instantiation}
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!Header}
//
// The first step required to use this filter is to include its header file.
//
// Software Guide : EndLatex
 
// Software Guide : BeginCodeSnippet
#include "itkDanielssonDistanceMapImageFilter.h"
// Software Guide : EndCodeSnippet
 
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkConnectedComponentImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
 
 
int
main(int argc, char * argv[])
{
  if (argc < 5)
  {
    std::cerr << "Usage: " << argv[0];
    std::cerr << " inputImageFile outputDistanceMapImageFile ";
    std::cerr << " outputVoronoiMapImageFile ";
    std::cerr << " outputVectorMapImageFile ";
    std::cerr << std::endl;
    return EXIT_FAILURE;
  }
 
  //  Software Guide : BeginLatex
  //
  //  Then we must decide what pixel types to use for the input and output
  //  images. Since the output will contain distances measured in pixels, the
  //  pixel type should be able to represent at least the width of the image,
  //  or said in $N$-dimensional terms, the maximum extension along all the
  //  dimensions. The input, output (distance map), and voronoi partition
  //  image types are now defined using their respective pixel type and
  //  dimension.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  using InputPixelType = unsigned char;
  using OutputPixelType = unsigned short;
  using VoronoiPixelType = unsigned char;
  using InputImageType = itk::Image<InputPixelType, 2>;
  using OutputImageType = itk::Image<OutputPixelType, 2>;
  using VoronoiImageType = itk::Image<VoronoiPixelType, 2>;
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  The filter type can be instantiated using the input and output image
  //  types defined above. A filter object is created with the \code{New()}
  //  method.
  //
  //  \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!instantiation}
  //  \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!New()}
  //  \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!Pointer}
  //
  //  Software Guide : EndLatex
 
  using LabelerType =
    itk::ConnectedComponentImageFilter<InputImageType, InputImageType>;
  LabelerType::Pointer labeler = LabelerType::New();
 
  // Software Guide : BeginCodeSnippet
  using FilterType = itk::DanielssonDistanceMapImageFilter<InputImageType,
                                                           OutputImageType,
                                                           VoronoiImageType>;
  FilterType::Pointer filter = FilterType::New();
  // Software Guide : EndCodeSnippet
 
  using RescalerType =
    itk::RescaleIntensityImageFilter<OutputImageType, OutputImageType>;
  RescalerType::Pointer scaler = RescalerType::New();
 
  using VoronoiRescalerType =
    itk::RescaleIntensityImageFilter<VoronoiImageType, VoronoiImageType>;
  VoronoiRescalerType::Pointer voronoiScaler = VoronoiRescalerType::New();
 
  //
  // Reader and Writer types are instantiated.
  //
  using ReaderType = itk::ImageFileReader<InputImageType>;
  using WriterType = itk::ImageFileWriter<OutputImageType>;
  using VoronoiWriterType = itk::ImageFileWriter<VoronoiImageType>;
 
  ReaderType::Pointer        reader = ReaderType::New();
  WriterType::Pointer        writer = WriterType::New();
  VoronoiWriterType::Pointer voronoiWriter = VoronoiWriterType::New();
 
  reader->SetFileName(argv[1]);
  writer->SetFileName(argv[2]);
  voronoiWriter->SetFileName(argv[3]);
 
 
  //  Software Guide : BeginLatex
  //
  //  The input to the filter is taken from a reader and its output is passed
  //  to a \doxygen{RescaleIntensityImageFilter} and then to a writer. The
  //  scaler and writer are both templated over the image type, so we
  //  instantiate a separate pipeline for the voronoi partition map starting
  //  at the scaler.
  //
  //  \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!SetInput()}
  //  \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!GetOutput()}
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  labeler->SetInput(reader->GetOutput());
  filter->SetInput(labeler->GetOutput());
  scaler->SetInput(filter->GetOutput());
  writer->SetInput(scaler->GetOutput());
  // Software Guide : EndCodeSnippet
 
  //  Software Guide : BeginLatex
  //
  //  The Voronoi map is obtained with the \code{GetVoronoiMap()} method. In
  //  the lines below we connect this output to the intensity rescaler.
  //
  //  \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!GetVoronoiMap()}
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  voronoiScaler->SetInput(filter->GetVoronoiMap());
  voronoiWriter->SetInput(voronoiScaler->GetOutput());
  // Software Guide : EndCodeSnippet
 
 
  scaler->SetOutputMaximum(65535L);
  scaler->SetOutputMinimum(0L);
  voronoiScaler->SetOutputMaximum(255);
  voronoiScaler->SetOutputMinimum(0);
 
  //  Software Guide : BeginLatex
  //
  // \begin{figure}
  // \center
  // \includegraphics[width=0.32\textwidth]{FivePointsDilated}
  // \includegraphics[width=0.32\textwidth]{DanielssonDistanceMapImageFilterOutput1}
  // \includegraphics[width=0.32\textwidth]{DanielssonDistanceMapImageFilterOutput2}
  // \itkcaption[DanielssonDistanceMapImageFilter
  // output]{DanielssonDistanceMapImageFilter output. Set of pixels, distance
  // map and Voronoi partition.}
  // \label{fig:DanielssonDistanceMapImageFilterInputOutput}
  // \end{figure}
  //
  //  Figure \ref{fig:DanielssonDistanceMapImageFilterInputOutput} illustrates
  //  the effect of this filter on a binary image with a set of points. The
  //  input image is shown at the left, and the distance map at the center and
  //  the Voronoi partition at the right. This filter computes distance maps
  //  in N-dimensions and is therefore capable of producing $N$-dimensional
  //  Voronoi partitions.
  //
  //  \index{Voronoi partitions}
  //  \index{Voronoi partitions!itk::Danielsson\-Distance\-Map\-Image\-Filter}
  //
  //  Software Guide : EndLatex
 
  writer->Update();
  voronoiWriter->Update();
 
  //  Software Guide : BeginLatex
  //
  //  The distance filter also produces an image of \doxygen{Offset} pixels
  //  representing the vectorial distance to the closest object in the scene.
  //  The type of this output image is defined by the VectorImageType
  //  trait of the filter type.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  using OffsetImageType = FilterType::VectorImageType;
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  We can use this type for instantiating an \doxygen{ImageFileWriter} type
  //  and creating an object of this class in the following lines.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  using WriterOffsetType = itk::ImageFileWriter<OffsetImageType>;
  WriterOffsetType::Pointer offsetWriter = WriterOffsetType::New();
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  The output of the distance filter can be connected as input to the
  //  writer.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  offsetWriter->SetInput(filter->GetVectorDistanceMap());
  // Software Guide : EndCodeSnippet
 
 
  offsetWriter->SetFileName(argv[4]);
 
 
  //  Software Guide : BeginLatex
  //
  //  Execution of the writer is triggered by the invocation of the
  //  \code{Update()} method. Since this method can potentially throw
  //  exceptions it must be placed in a \code{try/catch} block.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  try
  {
    offsetWriter->Update();
  }
  catch (const itk::ExceptionObject & exp)
  {
    std::cerr << "Exception caught !" << std::endl;
    std::cerr << exp << std::endl;
  }
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  Note that only the \doxygen{MetaImageIO} class supports reading and
  //  writing images of pixel type \doxygen{Offset}.
  //
  //  Software Guide : EndLatex
 
  return EXIT_SUCCESS;
}