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/*=========================================================================
*
* 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 : 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"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
// Software Guide : BeginLatex
//
// The header file corresponding to this filter should be included first.
//
// \index{itk::BinaryMedianImageFilter!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkBinaryMedianImageFilter.h"
// Software Guide : EndCodeSnippet
int main( int argc, char * argv[] )
{
if( argc < 4 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputImageFile radiusX radiusY" << 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
typedef unsigned char InputPixelType;
typedef unsigned char OutputPixelType;
typedef itk::Image< InputPixelType, 2 > InputImageType;
typedef itk::Image< OutputPixelType, 2 > OutputImageType;
// Software Guide : EndCodeSnippet
typedef itk::ImageFileReader< InputImageType > ReaderType;
typedef itk::ImageFileWriter< OutputImageType > WriterType;
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer writer = WriterType::New();
reader->SetFileName( argv[1] );
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
typedef itk::BinaryMedianImageFilter<
InputImageType, OutputImageType > FilterType;
FilterType::Pointer 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!Radius}
// \index{itk::BinaryMedianImageFilter!Neighborhood}
//
// Software Guide : EndLatex
const unsigned int radiusX = atoi( argv[3] );
const unsigned int radiusY = atoi( argv[4] );
// Software Guide : BeginCodeSnippet
InputImageType::SizeType indexRadius;
indexRadius[0] = radiusX; // radius along x
indexRadius[1] = radiusY; // radius along y
filter->SetRadius( indexRadius );
// 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
filter->SetInput( reader->GetOutput() );
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;
}
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