ITK  4.9.0
Insight Segmentation and Registration Toolkit
Examples/Filtering/RGBCurvatureAnisotropicDiffusionImageFilter.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: {VisibleWomanHeadSlice.png}
// OUTPUTS: {RGBCurvatureAnisotropicDiffusionImageFilterOutput.png}
// ARGUMENTS: 20 0.125
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// The vector anisotropic diffusion approach can be applied equally well to
// color images. As in the vector case, each RGB component is diffused
// independently. The following example illustrates the use of the
// \doxygen{VectorCurvatureAnisotropicDiffusionImageFilter} on an image with
// \doxygen{RGBPixel} type.
//
// \index{itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter!RGB Images}
//
// Software Guide : EndLatex
// Software Guide : BeginLatex
//
// The first step required to use this filter is to include its header file.
//
// \index{itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Also the headers for \code{Image} and \code{RGBPixel} type are required.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkRGBPixel.h"
#include "itkImage.h"
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// It is desirable to perform the computation on the RGB image using
// \code{float} representation. However for input and output purposes
// \code{unsigned char} RGB components are commonly used. It is necessary to
// cast the type of color components in the pipeline before writing them to
// a file. The \doxygen{VectorCastImageFilter} is used to achieve this goal.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
int main( int argc, char * argv[] )
{
if( argc < 5 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputRGBImageFile outputRGBImageFile ";
std::cerr << "numberOfIterations timeStep " << std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// The image type is defined using the pixel type and the dimension.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::RGBPixel< float > InputPixelType;
typedef itk::Image< InputPixelType, 2 > InputImageType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The filter type is now instantiated and a filter object is created by the
// \code{New()} method.
//
// \index{itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter!instantiation}
// \index{itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter!New()}
// \index{itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
InputImageType, InputImageType > FilterType;
FilterType::Pointer filter = FilterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The input image can be obtained from the output of another
// filter. Here, an image reader is used as a source.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( argv[1] );
filter->SetInput( reader->GetOutput() );
// Software Guide : EndCodeSnippet
const unsigned int numberOfIterations = atoi( argv[3] );
const double timeStep = atof( argv[4] );
// Software Guide : BeginLatex
//
// This filter requires two parameters: the number of iterations to be
// performed and the time step used in the computation of the level set
// evolution. These parameters are set using the methods
// \code{SetNumberOfIterations()} and \code{SetTimeStep()} respectively. The filter can
// be executed by invoking \code{Update()}.
//
// \index{itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter!Update()}
// \index{itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter!SetTimeStep()}
// \index{itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter!SetNumberOfIterations()}
// \index{SetTimeStep()!itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter}
// \index{SetNumberOfIterations()!itk::Vector\-Curvature\-Anisotropic\-Diffusion\-Image\-Filter}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetNumberOfIterations( numberOfIterations );
filter->SetTimeStep( timeStep );
filter->SetConductanceParameter(1.0);
filter->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The filter output is now cast to \code{unsigned char} RGB components by
// using the \doxygen{VectorCastImageFilter}.
//
// \index{itk::VectorCastImageFilter!instantiation}
// \index{itk::VectorCastImageFilter!New()}
// \index{itk::VectorCastImageFilter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::RGBPixel< unsigned char > WritePixelType;
typedef itk::Image< WritePixelType, 2 > WriteImageType;
InputImageType, WriteImageType > CasterType;
CasterType::Pointer caster = CasterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Finally, the writer type can be instantiated. One writer is created and
// connected to the output of the cast filter.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
WriterType::Pointer writer = WriterType::New();
caster->SetInput( filter->GetOutput() );
writer->SetInput( caster->GetOutput() );
writer->SetFileName( argv[2] );
writer->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// \begin{figure} \center
// \includegraphics[width=0.44\textwidth]{VisibleWomanHeadSlice}
// \includegraphics[width=0.44\textwidth]{RGBCurvatureAnisotropicDiffusionImageFilterOutput}
// \itkcaption[VectorCurvatureAnisotropicDiffusionImageFilter output on RGB]
// {Effect of the VectorCurvatureAnisotropicDiffusionImageFilter on a RGB
// image from a cryogenic section of the Visible Woman data set.}
// \label{fig:RGBVectorCurvatureAnisotropicDiffusionImageFilterInputOutput}
// \end{figure}
//
// Figure
// \ref{fig:RGBVectorCurvatureAnisotropicDiffusionImageFilterInputOutput}
// illustrates the effect of this filter on a RGB image from a cryogenic
// section of the Visible Woman data set. In this example the filter was
// run with a time step of $0.125$, and $20$ iterations. The input image
// has $570 \times 670$ pixels and the processing took $4$ minutes on a
// Pentium 4 at 2GHz.
//
// Software Guide : EndLatex
// Software Guide : BeginLatex
//
// \begin{figure} \center
// \includegraphics[width=0.32\textwidth]{VisibleWomanEyeSlice}
// \includegraphics[width=0.32\textwidth]{RGBGradientAnisotropicDiffusionImageFilterOutput2}
// \includegraphics[width=0.32\textwidth]{RGBCurvatureAnisotropicDiffusionImageFilterOutput2}
// \itkcaption[Various Anisotropic Diffusion compared] {Comparison between
// the gradient (center) and curvature (right) Anisotropic Diffusion filters.
// Original image at left.}
// \label{fig:ComparisionGradientCurvatureRGBAnisotropicDiffusion}
// \end{figure}
//
// Figure \ref{fig:ComparisionGradientCurvatureRGBAnisotropicDiffusion}
// compares the effect of the gradient and curvature anisotropic diffusion
// filters on a small region of the same cryogenic slice used in Figure
// \ref{fig:RGBVectorCurvatureAnisotropicDiffusionImageFilterInputOutput}.
// The region used in this figure is only $127 \times 162$ pixels and took
// $14$ seconds to compute on the same platform.
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}