Examples/IO/CovariantVectorImageWrite.cxx

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//  Software Guide : BeginLatex
//
//  This example illustrates how to write an image whose pixel type is
//  \code{CovariantVector}. For practical purposes all the content in this
//  example is applicable to images of pixel type \doxygen{Vector},
//  \doxygen{Point} and \doxygen{FixedArray}. These pixel types are similar
//  in that they are all arrays of fixed size in which the components have
//  the same representational type.
//
//  In order to make this example a bit more interesting we setup a pipeline
//  to read an image, compute its gradient and write the gradient to a file.
//  Gradients are represented with \doxygen{CovariantVector}s as opposed to
//  Vectors. In this way, gradients are transformed correctly under
//  \doxygen{AffineTransform}s or in general, any transform having
//  anisotropic scaling.
//
//  Let's start by including the relevant header files.
//
//  \index{ImageFileWriter!Vector images}
//
//  Software Guide : EndLatex
 
// Software Guide : BeginCodeSnippet
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
// Software Guide : EndCodeSnippet
 
 
//  Software Guide : BeginLatex
//
//  We use the \doxygen{GradientRecursiveGaussianImageFilter} in order to
//  compute the image gradient. The output of this filter is an image whose
//  pixels are CovariantVectors.
//
//  \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter!header}
//
//  Software Guide : EndLatex
 
// Software Guide : BeginCodeSnippet
#include "itkGradientRecursiveGaussianImageFilter.h"
// Software Guide : EndCodeSnippet
 
 
int
main(int argc, char ** argv)
{
  // Verify the number of parameters in the command line
  if (argc < 3)
  {
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0] << " inputImageFile  outputVectorImageFile "
              << std::endl;
    return EXIT_FAILURE;
  }
 
 
  //  Software Guide : BeginLatex
  //
  //  We read an image of \code{short} pixels and compute the
  //  gradient to produce an image of CovariantVectors where each
  //  component is of type \code{float}.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  using InputPixelType = short;
  using ComponentType = float;
  constexpr unsigned int Dimension = 2;
 
  using OutputPixelType = itk::CovariantVector<ComponentType, Dimension>;
 
  using InputImageType = itk::Image<InputPixelType, Dimension>;
  using OutputImageType = itk::Image<OutputPixelType, Dimension>;
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  The \doxygen{ImageFileReader} and \doxygen{ImageFileWriter} are
  //  instantiated using the image types.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  using ReaderType = itk::ImageFileReader<InputImageType>;
  using WriterType = itk::ImageFileWriter<OutputImageType>;
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  The GradientRecursiveGaussianImageFilter class is instantiated
  //  using the input and output image types. A filter object is created with
  //  the \code{New()} method and assigned to a \doxygen{SmartPointer}.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  using FilterType =
    itk::GradientRecursiveGaussianImageFilter<InputImageType,
                                              OutputImageType>;
 
  auto filter = FilterType::New();
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  We select a value for the $\sigma$ parameter of the
  //  GradientRecursiveGaussianImageFilter. Note that $\sigma$
  //  for this filter is specified in millimeters.
  //
  //  Software Guide : EndLatex
 
 
  // Software Guide : BeginCodeSnippet
  filter->SetSigma(1.5); // Sigma in millimeters
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  Below, we create the reader and writer using the \code{New()} method and
  //  assign the result to a \doxygen{SmartPointer}.
  //
  //  \index{itk::ImageFileReader!New()}
  //  \index{itk::ImageFileWriter!New()}
  //  \index{itk::ImageFileReader!SmartPointer}
  //  \index{itk::ImageFileWriter!SmartPointer}
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  auto reader = ReaderType::New();
  auto writer = WriterType::New();
  // Software Guide : EndCodeSnippet
 
 
  //
  // Here we recover the file names from the command line arguments
  //
  const char * inputFilename = argv[1];
  const char * outputFilename = argv[2];
 
 
  //  Software Guide : BeginLatex
  //
  //  The name of the file to be read or written is passed to the
  //  \code{SetFileName()} method.
  //
  //  \index{itk::ImageFileReader!SetFileName()}
  //  \index{itk::ImageFileWriter!SetFileName()}
  //  \index{SetFileName()!itk::ImageFileReader}
  //  \index{SetFileName()!itk::ImageFileWriter}
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  reader->SetFileName(inputFilename);
  writer->SetFileName(outputFilename);
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  Below we connect the reader, filter and writer to form the data
  //  processing pipeline.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  filter->SetInput(reader->GetOutput());
  writer->SetInput(filter->GetOutput());
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  Finally we execute the pipeline by invoking \code{Update()} on the
  //  writer. The call is placed in a \code{try/catch} block in case
  //  exceptions are thrown.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  try
  {
    writer->Update();
  }
  catch (const itk::ExceptionObject & err)
  {
    std::cerr << "ExceptionObject caught !" << std::endl;
    std::cerr << err << std::endl;
    return EXIT_FAILURE;
  }
  // Software Guide : EndCodeSnippet
 
 
  return EXIT_SUCCESS;
}