ITK  4.13.0
Insight Segmentation and Registration Toolkit
Examples/Filtering/MedianImageFilter.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 : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// OUTPUTS: {MedianImageFilterOutput.png}
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// The \doxygen{MedianImageFilter} is commonly used as a robust approach for
// noise reduction. This filter is particularly efficient against
// \emph{salt-and-pepper} noise. In other words, it is robust to the presence
// of gray-level outliers. MedianImageFilter computes the value of each output
// pixel as the statistical median of the neighborhood of values around the
// corresponding input pixel. The following figure illustrates the local
// effect of this filter in a $2D$ case. The statistical median of the
// neighborhood on the left is passed as the output value associated with the
// pixel at the center of the neighborhood.
//
//
// \begin{center}
// \begin{picture}(200,46)
// \put( 5.0, 0.0 ){\framebox(30.0,15.0){25}}
// \put( 35.0, 0.0 ){\framebox(30.0,15.0){30}}
// \put( 65.0, 0.0 ){\framebox(30.0,15.0){32}}
// \put( 5.0, 15.0 ){\framebox(30.0,15.0){27}}
// \put( 35.0, 15.0 ){\framebox(30.0,15.0){25}}
// \put( 65.0, 15.0 ){\framebox(30.0,15.0){29}}
// \put( 5.0, 30.0 ){\framebox(30.0,15.0){28}}
// \put( 35.0, 30.0 ){\framebox(30.0,15.0){26}}
// \put( 65.0, 30.0 ){\framebox(30.0,15.0){50}}
// \put( 100.0, 22.0 ){\vector(1,0){20.0}}
// \put( 125.0, 15.0 ){\framebox(30.0,15.0){28}}
// \end{picture}
// \end{center}
//
//
// 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::MedianImageFilter}
//
// Software Guide : EndLatex
// Software Guide : BeginLatex
//
// The header file corresponding to this filter should be included first.
//
// \index{itk::MedianImageFilter!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
int main( int argc, char * argv[] )
{
if( argc < 3 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputImageFile" << 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
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::MedianImageFilter!instantiation}
// \index{itk::MedianImageFilter!New()}
// \index{itk::MedianImageFilter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
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::MedianImageFilter!Radius}
// \index{itk::MedianImageFilter!Neighborhood}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
indexRadius[0] = 1; // radius along x
indexRadius[1] = 1; // 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::MedianImageFilter!SetInput()}
// \index{itk::MedianImageFilter!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]{BrainProtonDensitySlice}
// \includegraphics[width=0.44\textwidth]{MedianImageFilterOutput}
// \itkcaption[Effect of the Median filter.]{Effect of the MedianImageFilter on a
// slice from a MRI proton density brain image.}
// \label{fig:MedianImageFilterOutput}
// \end{figure}
//
// Figure \ref{fig:MedianImageFilterOutput} illustrates the effect of the MedianImageFilter
// filter on a slice of MRI brain image using a neighborhood radius of
// \(1,1\), which corresponds to a $ 3 \times 3 $ classical neighborhood.
// The filtered image demonstrates the moderate tendency of the median
// filter to preserve edges.
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}