ITK  5.4.0 Insight Toolkit
Examples/Filtering/BinaryMedianImageFilter.cxx
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// Software Guide : BeginCommandLineArgs
// INPUTS: {BinaryThresholdImageFilterOutput.png}
// OUTPUTS: {BinaryMedianImageFilterOutput.png}
// ARGUMENTS: 2 2
// Software Guide : EndCommandLineArgs
//
// BinaryThresholdImageFilterOutput.png was obtained from the
// BinaryThreshold ImageFilter example.
//
// Software Guide : BeginLatex
//
// The \doxygen{BinaryMedianImageFilter} is commonly used as a robust
// approach for noise reduction. BinaryMedianImageFilter computes the value
// of each output pixel as the statistical median of the neighborhood of
// values around the corresponding input pixel. When the input images are
// binary, the implementation can be optimized by simply counting the number
// of pixels ON/OFF around the current pixel.
//
// This filter will work on images of any dimension thanks to the internal
// use of \doxygen{NeighborhoodIterator} and \doxygen{NeighborhoodOperator}.
// The size of the neighborhood over which the median is computed can be set
// by the user.
//
// \index{itk::BinaryMedianImageFilter}
//
// Software Guide : EndLatex
#include "itkImage.h"
// Software Guide : BeginLatex
//
// The header file corresponding to this filter should be included first.
//
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
int
main(int argc, char * argv[])
{
if (argc < 4)
{
std::cerr << "Usage: " << std::endl;
<< std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// Then the pixel and image types of the input and output must be defined.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using InputPixelType = unsigned char;
using OutputPixelType = unsigned char;
using InputImageType = itk::Image<InputPixelType, 2>;
using OutputImageType = itk::Image<OutputPixelType, 2>;
// Software Guide : EndCodeSnippet
auto writer = WriterType::New();
writer->SetFileName(argv[2]);
// Software Guide : BeginLatex
//
// Using the image types, it is now possible to define the filter type
// and create the filter object.
//
// \index{itk::BinaryMedianImageFilter!instantiation}
// \index{itk::BinaryMedianImageFilter!New()}
// \index{itk::BinaryMedianImageFilter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using FilterType =
auto filter = FilterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The size of the neighborhood is defined along every dimension by
// passing a \code{SizeType} object with the corresponding values. The
// value on each dimension is used as the semi-size of a rectangular
// box. For example, in $2D$ a size of $$1,2$$ will result in a $3 \times // 5$ neighborhood.
//
// \index{itk::BinaryMedianImageFilter!Neighborhood}
//
// Software Guide : EndLatex
const unsigned int radiusX = std::stoi(argv[3]);
const unsigned int radiusY = std::stoi(argv[4]);
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The input to the filter can be taken from any other filter, for example
// a reader. The output can be passed down the pipeline to other filters,
// for example, a writer. An update call on any downstream filter will
// trigger the execution of the median filter.
//
// \index{itk::BinaryMedianImageFilter!SetInput()}
// \index{itk::BinaryMedianImageFilter!GetOutput()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
writer->SetInput(filter->GetOutput());
writer->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// \begin{figure}
// \center
// \includegraphics[width=0.44\textwidth]{BinaryThresholdImageFilterOutput}
// \includegraphics[width=0.44\textwidth]{BinaryMedianImageFilterOutput}
// \itkcaption[Effect of the BinaryMedian filter.]{Effect of the
// BinaryMedianImageFilter on a slice from a MRI proton density brain image
// that has been thresholded in order to produce a binary image.}
// \label{fig:BinaryMedianImageFilterOutput}
// \end{figure}
//
// Figure \ref{fig:BinaryMedianImageFilterOutput} illustrates the effect of
// the BinaryMedianImageFilter filter on a slice of MRI brain image using a
// neighborhood radius of $$2,2$$, which corresponds to a $5 \times 5$
// classical neighborhood. The filtered image demonstrates the capability
// of this filter for reducing noise both in the background and foreground
// of the image, as well as smoothing the contours of the regions.
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}
itk::BinaryMedianImageFilter
Applies a version of the median filter optimized for binary images.
Definition: itkBinaryMedianImageFilter.h:50
itk::GTest::TypedefsAndConstructors::Dimension2::SizeType
ImageBaseType::SizeType SizeType
Definition: itkGTestTypedefsAndConstructors.h:49
itkImage.h