ITK  5.0.0
Insight Segmentation and Registration Toolkit
Examples/IO/CovariantVectorImageWrite.cxx
/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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
*
* http://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 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
// 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
// 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{signed 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 = signed short;
using ComponentType = float;
constexpr unsigned int Dimension = 2;
using OutputPixelType = itk::CovariantVector< ComponentType,
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
// 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
InputImageType,
OutputImageType >;
FilterType::Pointer 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
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer 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( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
// Software Guide : EndCodeSnippet
return EXIT_SUCCESS;
}