/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: RGBGradientAnisotropicDiffusionImageFilter.cxx,v $
  Language:  C++
  Date:      $Date: 2005/08/31 13:55:22 $
  Version:   $Revision: 1.27 $

  Copyright (c) Insight Software Consortium. All rights reserved.
  See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.

     This software is distributed WITHOUT ANY WARRANTY; without even 
     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR 
     PURPOSE.  See the above copyright notices for more information.

=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif

#ifdef __BORLANDC__
#define ITK_LEAN_AND_MEAN
#endif

//  Software Guide : BeginCommandLineArgs
//  INPUTS: {VisibleWomanHeadSlice.png}
//  OUTPUTS: {RGBGradientAnisotropicDiffusionImageFilterOutput.png}
//  20 0.125
//  Software Guide : EndCommandLineArgs

//  Software Guide : BeginLatex
//
//  The vector anisotropic diffusion approach can equally well be applied to
//  color images. As in the vector case, each RGB component is diffused
//  independently. The following example illustrates the use of the Vector
//  curvature anisotropic diffusion filter on an image with
//  \doxygen{RGBPixel} type.
//
//  \index{itk::Vector\-Gradient\-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\-Gradient\-Anisotropic\-Diffusion\-Image\-Filter!header}
//
//  Software Guide : EndLatex 

// Software Guide : BeginCodeSnippet
#include "itkVectorGradientAnisotropicDiffusionImageFilter.h"
// 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 along the pipeline before writing them
//  to a file. The \doxygen{VectorCastImageFilter} is used to achieve this
//  goal.
//
//  Software Guide : EndLatex 

// Software Guide : BeginCodeSnippet
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkVectorCastImageFilter.h"
// 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\-Gradient\-Anisotropic\-Diffusion\-Image\-Filter!instantiation}
  //  \index{itk::Vector\-Gradient\-Anisotropic\-Diffusion\-Image\-Filter!New()}
  //  \index{itk::Vector\-Gradient\-Anisotropic\-Diffusion\-Image\-Filter!Pointer}
  //
  //  Software Guide : EndLatex 

  // Software Guide : BeginCodeSnippet
  typedef itk::VectorGradientAnisotropicDiffusionImageFilter<
                       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 source.
  //
  //  Software Guide : EndLatex 

  // Software Guide : BeginCodeSnippet
  typedef itk::ImageFileReader< InputImageType >  ReaderType;
  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\-Gradient\-Anisotropic\-Diffusion\-Image\-Filter!Update()}
  //  \index{itk::Vector\-Gradient\-Anisotropic\-Diffusion\-Image\-Filter!SetTimeStep()}
  //  \index{itk::Vector\-Gradient\-Anisotropic\-Diffusion\-Image\-Filter!SetNumberOfIterations()}
  //  \index{SetTimeStep()!itk::Vector\-Gradient\-Anisotropic\-Diffusion\-Image\-Filter}
  //  \index{SetNumberOfIterations()!itk::Vector\-Gradient\-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;
  typedef itk::VectorCastImageFilter< 
                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
  typedef itk::ImageFileWriter< WriteImageType >  WriterType;
  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.eps}
  // \includegraphics[width=0.44\textwidth]{RGBGradientAnisotropicDiffusionImageFilterOutput.eps}
  // \itkcaption[VectorGradientAnisotropicDiffusionImageFilter on RGB] {Effect of
  // the VectorGradientAnisotropicDiffusionImageFilter on a RGB image from a
  // cryogenic section of the Visible Woman data set.}
  // \label{fig:RGBVectorGradientAnisotropicDiffusionImageFilterInputOutput}
  // \end{figure}
  //
  //  Figure
  //  \ref{fig:RGBVectorGradientAnisotropicDiffusionImageFilterInputOutput}
  //  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 2Ghz.
  //
  //  Software Guide : EndLatex 

  return EXIT_SUCCESS;
}

